International Journal of Modern Engineering Research (IJMER) is Peer reviewed, online Journal. It serves as an international archival forum of scholarly research related to engineering and science education.
Social network has become so popular with overwhelming high rate of growth, due to this popularity the online social networks is facing the issues of spamming, which has leads to unsubstantial economic loss to this menace of spam and spammers activities. It has leads to uncontrollable dissemination of viruses and malwares, promotional ads, phishing, and scams. spam activities has enter a new dangerous dimension, the spammers have step up their games and tactics online social networks, it consumes large amounts of network bandwidth leading to less revenue and significant economic loss to both private and public sectors. From the previous scholars work on spammer classification taxonomy, various machine learning techniques have been extensively used to detect spam activities and spammers in online social networks. There are various classifier that are learn over content-based features extracted from the user's interactions and profiles to label them as spam/spammers or legitimate. But recently, new network structural bench mark features have been proposed for spammer detection task, but their importance using structural bench mark learning methods has not been extensively evaluated yet. In this research work, we evaluate the the metric performance of some structural bench mark learning methods using scientific and strategic approach based attributes extracted from an interaction network for the task of spammer detection in online social network.
Detecting Spam Tags Against Collaborative Unfair Through Trust ModellingIOSR Journals
This document discusses methods for detecting spam tags in collaborative tagging systems through trust modeling. It classifies existing approaches into content trust modeling and user trust modeling. Content trust modeling assigns trust scores to content based on tags and users associated with it, while user trust modeling assigns trust scores to users based on their tagging behavior. The document also discusses challenges like evaluating models on multilingual data and lack of publicly available datasets for comparison. It concludes that trust modeling is important for enhancing reliability of social networks and content sharing services.
Authorization mechanism for multiparty data sharing in social networkeSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
An Approach to Detect and Avoid Social Engineering and Phasing Attack in Soci...IJASRD Journal
Digital physical frameworks are the key advancement driver for some spaces, for example, car, flight, mechanical procedure control, and industrial facility mechanization. Be that as it may, their interconnection possibly gives enemies simple access to delicate information, code, and setups. In the event that aggressors gain control, material harm or even damage to individuals must be normal. To neutralize information burglary, framework control and digital assaults, security instruments must be implanted in the digital physical framework. The social building assault layouts are changed over to social designing assault situations by populating the format with the two subjects and articles from genuine precedents while as yet keeping up the point by point stream of the assault as gave in the format. Social Engineering by E-Mail is by a wide margin the most intensely utilized vector of assault, trailed by assaults beginning from sites. The aggressor in this way misuses the set up trust by requesting that consent utilize the organization's remote system office to send an email. A social designer can likewise join mechanical intends to accomplish the assault goals. The heuristic-based discovery method examines and separates phishing site includes and recognizes phishing locales utilizing that data .Based on the robotized examination of the record in the informal organization, you can construct suppositions about the power of correspondence between clients. In view of this data, it is conceivable to compute the likelihood of achievement of a multistep social building assault from the client to the client in digital physical/digital social framework. Furthermore, the proposed social designing assault layouts can likewise be utilized to create social building mindfulness material.
Identification of inference attacks on private Information from Social Networkseditorjournal
Online social networks, like
Facebook, twitter are increasingly utilized by
many people. These networks permit users to
publish details about them and to connect to
their friends. Some of the details revealed
inside these networks are meant to be
keeping private. Yet it is possible to use
learning algorithms and methods on released
data have to predict private information,
which cause inference attacks. This paper
discovers how to launch inference attacks
using released social networking details to
predict private information’s. It then
separate three possible sanitization
algorithms that could be used in various
situations. Then, it investigates the
effectiveness of these techniques and tries to
use methods of collective inference
techniques to determine sensitive attributes
of the user data set. It shows that it can
decline the effectiveness of both the local and
relational classification algorithms by using
the sanitization methods we described.
MDS 2011 Paper: An Unsupervised Approach to Discovering and Disambiguating So...Carlton Northern
This document presents an unsupervised approach to discover and disambiguate social media profiles for a large group of individuals, such as employees or university students. The approach uses a combination of search engine queries, semantic web queries, and directly polling social media sites to discover potential profiles. It then applies heuristics involving keyword matching, community structure analysis, and extracting semantic and profile features to disambiguate the true profiles from false positives. The approach was tested on a set of 2016 university computer science student logins, achieving a precision of 0.863 and F-measure of 0.654 at discovering their real social media profiles from a ground truth data set.
Attacking the Privacy of Social Network users (HITB 2011)Marco Balduzzi
The document summarizes research into attacking the privacy of social network users. It describes how the researcher was able to automatically query social networks to map email addresses to user profiles and correlate information across networks. Experiments showed this could profile over 10 million users, discovering inconsistencies. The researcher also demonstrated how to leverage friend networks through techniques like reverse social engineering and drive-by downloads. Finally, alternatives like a decentralized "Safebook" social network are proposed to address privacy and security issues.
How to Make People Click on a Dangerous Link Despite their Security Awareness mark-smith
It is possible to make virtually any person click on a link, as any person will be curious about something, or interested in some topic, or find the message plausible because they know the sender, or because it fits their expectations (context).
Social network has become so popular with overwhelming high rate of growth, due to this popularity the online social networks is facing the issues of spamming, which has leads to unsubstantial economic loss to this menace of spam and spammers activities. It has leads to uncontrollable dissemination of viruses and malwares, promotional ads, phishing, and scams. spam activities has enter a new dangerous dimension, the spammers have step up their games and tactics online social networks, it consumes large amounts of network bandwidth leading to less revenue and significant economic loss to both private and public sectors. From the previous scholars work on spammer classification taxonomy, various machine learning techniques have been extensively used to detect spam activities and spammers in online social networks. There are various classifier that are learn over content-based features extracted from the user's interactions and profiles to label them as spam/spammers or legitimate. But recently, new network structural bench mark features have been proposed for spammer detection task, but their importance using structural bench mark learning methods has not been extensively evaluated yet. In this research work, we evaluate the the metric performance of some structural bench mark learning methods using scientific and strategic approach based attributes extracted from an interaction network for the task of spammer detection in online social network.
Detecting Spam Tags Against Collaborative Unfair Through Trust ModellingIOSR Journals
This document discusses methods for detecting spam tags in collaborative tagging systems through trust modeling. It classifies existing approaches into content trust modeling and user trust modeling. Content trust modeling assigns trust scores to content based on tags and users associated with it, while user trust modeling assigns trust scores to users based on their tagging behavior. The document also discusses challenges like evaluating models on multilingual data and lack of publicly available datasets for comparison. It concludes that trust modeling is important for enhancing reliability of social networks and content sharing services.
Authorization mechanism for multiparty data sharing in social networkeSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
An Approach to Detect and Avoid Social Engineering and Phasing Attack in Soci...IJASRD Journal
Digital physical frameworks are the key advancement driver for some spaces, for example, car, flight, mechanical procedure control, and industrial facility mechanization. Be that as it may, their interconnection possibly gives enemies simple access to delicate information, code, and setups. In the event that aggressors gain control, material harm or even damage to individuals must be normal. To neutralize information burglary, framework control and digital assaults, security instruments must be implanted in the digital physical framework. The social building assault layouts are changed over to social designing assault situations by populating the format with the two subjects and articles from genuine precedents while as yet keeping up the point by point stream of the assault as gave in the format. Social Engineering by E-Mail is by a wide margin the most intensely utilized vector of assault, trailed by assaults beginning from sites. The aggressor in this way misuses the set up trust by requesting that consent utilize the organization's remote system office to send an email. A social designer can likewise join mechanical intends to accomplish the assault goals. The heuristic-based discovery method examines and separates phishing site includes and recognizes phishing locales utilizing that data .Based on the robotized examination of the record in the informal organization, you can construct suppositions about the power of correspondence between clients. In view of this data, it is conceivable to compute the likelihood of achievement of a multistep social building assault from the client to the client in digital physical/digital social framework. Furthermore, the proposed social designing assault layouts can likewise be utilized to create social building mindfulness material.
Identification of inference attacks on private Information from Social Networkseditorjournal
Online social networks, like
Facebook, twitter are increasingly utilized by
many people. These networks permit users to
publish details about them and to connect to
their friends. Some of the details revealed
inside these networks are meant to be
keeping private. Yet it is possible to use
learning algorithms and methods on released
data have to predict private information,
which cause inference attacks. This paper
discovers how to launch inference attacks
using released social networking details to
predict private information’s. It then
separate three possible sanitization
algorithms that could be used in various
situations. Then, it investigates the
effectiveness of these techniques and tries to
use methods of collective inference
techniques to determine sensitive attributes
of the user data set. It shows that it can
decline the effectiveness of both the local and
relational classification algorithms by using
the sanitization methods we described.
MDS 2011 Paper: An Unsupervised Approach to Discovering and Disambiguating So...Carlton Northern
This document presents an unsupervised approach to discover and disambiguate social media profiles for a large group of individuals, such as employees or university students. The approach uses a combination of search engine queries, semantic web queries, and directly polling social media sites to discover potential profiles. It then applies heuristics involving keyword matching, community structure analysis, and extracting semantic and profile features to disambiguate the true profiles from false positives. The approach was tested on a set of 2016 university computer science student logins, achieving a precision of 0.863 and F-measure of 0.654 at discovering their real social media profiles from a ground truth data set.
Attacking the Privacy of Social Network users (HITB 2011)Marco Balduzzi
The document summarizes research into attacking the privacy of social network users. It describes how the researcher was able to automatically query social networks to map email addresses to user profiles and correlate information across networks. Experiments showed this could profile over 10 million users, discovering inconsistencies. The researcher also demonstrated how to leverage friend networks through techniques like reverse social engineering and drive-by downloads. Finally, alternatives like a decentralized "Safebook" social network are proposed to address privacy and security issues.
How to Make People Click on a Dangerous Link Despite their Security Awareness mark-smith
It is possible to make virtually any person click on a link, as any person will be curious about something, or interested in some topic, or find the message plausible because they know the sender, or because it fits their expectations (context).
The document discusses a study that examines the correlation between actor centrality in social networks and their ability to coordinate projects. It outlines the research framework, which involves extracting coordination-related phrases from emails, calculating coordination scores bounded by project scopes, constructing social network matrices using centrality measures, and testing the association between centrality and coordination. Preliminary results on the Enron email network from 1997-2002 are presented. The methodology involves text mining the Enron dataset to calculate coordination scores and social network centrality metrics like degree, closeness, and betweenness centrality.
The document summarizes a research paper that proposes a personalized recommendation approach combining social network factors like interpersonal interest similarity and interpersonal rating behavior similarity. It uses probabilistic matrix factorization to predict ratings by considering these social network factors. The approach is evaluated on two large real-world social rating datasets and shows improved performance over approaches that only use social network information.
An iac approach for detecting profile cloningIJNSA Journal
Nowadays, Online Social Networks (OSNs) are popular websites on the internet, which millions of users
register on and share their own personal information with others. Privacy threats and disclosing personal
information are the most important concerns of OSNs’ users. Recently, a new attack which is named
Identity Cloned Attack is detected on OSNs. In this attack the attacker tries to make a fake identity of a real
user in order to access to private information of the users’ friends which they do not publish on the public
profiles. In today OSNs, there are some verification services, but they are not active services and they are
useful for users who are familiar with online identity issues. In this paper, Identity cloned attacks are
explained in more details and a new and precise method to detect profile cloning in online social networks
is proposed. In this method, first, the social network is shown in a form of graph, then, according to
similarities among users, this graph is divided into smaller communities. Afterwards, all of the similar
profiles to the real profile are gathered (from the same community), then strength of relationship (among
all selected profiles and the real profile) is calculated, and those which have the less strength of
relationship will be verified by mutual friend system. In this study, in order to evaluate the effectiveness of
proposed method, all steps are applied on a dataset of Facebook, and finally this work is compared with
two previous works by applying them on the dataset.
International Journal of Engineering Research and DevelopmentIJERD Editor
Electrical, Electronics and Computer Engineering,
Information Engineering and Technology,
Mechanical, Industrial and Manufacturing Engineering,
Automation and Mechatronics Engineering,
Material and Chemical Engineering,
Civil and Architecture Engineering,
Biotechnology and Bio Engineering,
Environmental Engineering,
Petroleum and Mining Engineering,
Marine and Agriculture engineering,
Aerospace Engineering.
This document summarizes a research paper that presents a reputation system called Tulungan designed to measure contributor and rater reputation in collaborative web filtering systems. Tulungan aims to be resistant to slandering attacks, where malicious raters intentionally give inaccurate negative ratings. The paper describes Tulungan's algorithm, which initializes reputations and allows contributions, rating, and reputation computation in cycles. A simulation evaluates Tulungan in the presence of good, malicious, and slandering users, finding that Tulungan is effective even when good users are a minority and is resistant to slandering.
Social Networking Sites have become the means of the communication and have
experienced growth in the recent years. As these sites offer services for free of costs are
attracting the people all around the world. Some technologies are emerging in the field of
Internet but still the users are facing the security leakages by unauthorized users. Many of
the Social Sites are managed by the Third Party Domains which keep track of all the user
information along with the access details. Most Online Social Networking (OSN) Sites
provide an “accept all or nothing” mechanism for managing permission from Third Party
Access (TPA) to access user’s private data [3]. The Social Media sites do not provide any
mechanism for privacy on the shared data among the multiple users. Many users share their
personal information without knowing about the cyber thefts and risks associated with it.
From the survey it has been found that the teenagers are least concerned about the
navigating privacy. Privacy associated with the Social media is the very crucial thing.
Different methods are discussed regarding sharing of the personal information and leakage
of this information through different mediums. Different models are also proposed in this
paper regarding the privacy control of third party access of the personal information. An
approach is proposed which allows users to share their access control configuration for TPA
s with their friends who can reuse and rate such configurations [3]
1) The document discusses predicting the strength of ties between individuals in online social networks using measures of their ego network structures. It analyzes how factors like degree centrality, betweenness centrality, and dispersion within ego networks correlate with perceived tie strength.
2) An empirical study collected data on Facebook ego networks and tie strength perceptions from 41 respondents. Network measures like betweenness in ego networks were highly predictive of close ties.
3) The findings suggest that ego network analyses can reveal close friendships even without direct disclosure of that information, with implications for data privacy, understanding peer influence, and analyzing other networked data.
An Access Control Model for Collaborative Management of Shared Data in OSNSIJMER
This document presents a multi-party access control model for managing shared data in online social networks. It proposes that access control policies for shared data should be specified collaboratively by multiple associated users, not just the data owner. An access control policy format is defined that includes the controller, controller type, accessor, data specification, and authorization effect. A prototype application called MController is implemented that allows multiple users to specify access control policies and resolve conflicts for shared photos. An evaluation of MController found that users had a more positive view of its privacy controls compared to Facebook's default controls. Performance testing showed the policy evaluation mechanism scaled well as the number of controllers increased.
The document summarizes research issues, tools, and applications related to analyzing the blogosphere. It discusses how social networks form online through blogs and user-generated content. Various approaches are presented for modeling, analyzing, and mining the blogosphere to study influence, communities, and other phenomena. Tools and methods mentioned include network analysis, text mining, and simulating the blogosphere as a complex social network with nodes and relationships.
IRJET- Effective Countering of Communal Hatred During Disaster Events in Soci...IRJET Journal
This document summarizes a research paper that aims to effectively counter communal hatred during disaster events on social media. It uses machine learning techniques to analyze tweets and classify them based on parameters like offensive, hatred, or neither. Tweets are collected using Twitter's API and preprocessed. A supervised machine learning algorithm (Support Vector Machine) is trained on manually labeled tweet data to classify new tweets. The results are visualized in a pie chart graph displaying the percentage of tweets containing offensive, hatred, or neutral words. The goal is to reduce the spread of communal hate speech on social media during disasters.
This document discusses using trust and provenance for content filtering on the semantic web. It describes how trust can be inferred between individuals in social networks and how that trust information can be used to filter and recommend content. Applications mentioned include using trust ratings to help intelligence analysts sort through information by identifying reliable sources.
The document presents the technical design for a social networking site called AMBA. It aims to address security and privacy issues with current sites by reducing the availability of personal information. It will assign each user a unique PIN that must be shared to add friends or view profiles. Searching by name will not show results, only by PIN. The design includes user registration, login, profile creation, friend requests, and posting features. It will use a SQL Server database to store user data and Visual Studio for development. The high-level design seeks to make the site less "stalker friendly" while still enabling social connections.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
The document discusses how recommender systems are evolving with the rise of Web 2.0 and social media platforms. It outlines how these new platforms provide more user data like demographics, social connections, tags, and folksonomies that can be used to develop new and improved recommendation algorithms. Specifically, it discusses how trust between users and exploiting the social graph can help with challenges like cold starts and attacks. It also examines using tags for content-based and collaborative filtering recommendations. Overall, the integration of social media data and semantic approaches is leading to more personalized and higher quality recommendations.
My Privacy My decision: Control of Photo Sharing on Online Social NetworksIRJET Journal
This document summarizes a research paper that proposes a facial recognition system to help users control photo sharing on social networks while protecting privacy. It discusses how photo sharing on social networks can unintentionally reveal private user information through tags, comments or metadata. The proposed system would recognize faces in photos and allow users to choose privacy settings during the photo posting process. It would also use private user photos to train the facial recognition model while preserving privacy through a distributed consensus method. The goal is to give users more awareness and control over how their photos are shared and help prevent unintended disclosure of personal information.
IRJET- Fake Profile Identification using Machine LearningIRJET Journal
This document proposes a framework for identifying fake profiles on social media sites using machine learning. It involves selecting profile attributes from a dataset, training a random forest classifier model on 80% of the labeled real and fake profiles, and testing it on the remaining 20%. The random forest classifier is able to accurately classify profiles as real or fake with an efficiency of 95% based on attributes like number of friends, followers, and status updates. This automatic fake profile detection method could help social media sites manage the large volume of profiles that can't be manually reviewed.
IRJET- Tweet Segmentation and its Application to Named Entity RecognitionIRJET Journal
This document summarizes a research paper on tweet segmentation and its application to named entity recognition. It proposes a novel framework called Hybrid Segmentation that splits tweets into meaningful segments to preserve semantic context for downstream natural language processing applications like named entity recognition. HybridSeg finds optimal tweet segmentations by maximizing the stickiness score of segments, which considers global context based on English phrases and local context based on linguistic features or term dependencies within a batch of tweets. Experiments show significantly improved segmentation quality when learning both global and local contexts compared to global context alone. The segmented tweets can then be used for high accuracy named entity recognition through part-of-speech tagging.
This document discusses the selection and placement of various photographs in a magazine. It analyzes 6 different photos, describing where each would be placed and the reasons for choosing them. The reasons generally include liking the poses, costumes, framing, lighting, colors, composition and clarity of the images. Providing insight into the subjects and fitting nicely with the text or layout are also mentioned.
This document contains two short phrases: "38 group" and "Nino talabadze". It does not provide enough context or details to generate a meaningful multi-sentence summary. The document appears to list a group name and a person's name but without additional context around what they refer to or their significance.
This document summarizes a research paper that introduces a new class of complex-valued harmonic functions. The paper defines a generalized derivative operator for harmonic functions with varying arguments. It obtains a sufficient coefficient condition for functions to belong to the proposed class of starlike harmonic functions. It also shows that the coefficient condition is necessary for functions in the subclass of harmonic functions with varying arguments. The paper derives extreme points for functions in this subclass.
This document summarizes a research paper that proposes global block-based redundancy architectures for self-repairing of embedded memories. The key points are:
- Redundant rows and columns of memory are divided into blocks that can replace faulty blocks anywhere in the memory array, rather than just within the same row or column. This global approach helps repair clustered faults.
- A modified essential spare pivoting (MESP) algorithm is proposed for built-in redundancy analysis that has low area overhead. It collects faulty cell information and analyzes block-level faults.
- Simulation results show the proposed architectures and MESP algorithm significantly improve manufacturing yield, repair rates, and reliability compared to other approaches, due to their efficient
The document discusses a study that examines the correlation between actor centrality in social networks and their ability to coordinate projects. It outlines the research framework, which involves extracting coordination-related phrases from emails, calculating coordination scores bounded by project scopes, constructing social network matrices using centrality measures, and testing the association between centrality and coordination. Preliminary results on the Enron email network from 1997-2002 are presented. The methodology involves text mining the Enron dataset to calculate coordination scores and social network centrality metrics like degree, closeness, and betweenness centrality.
The document summarizes a research paper that proposes a personalized recommendation approach combining social network factors like interpersonal interest similarity and interpersonal rating behavior similarity. It uses probabilistic matrix factorization to predict ratings by considering these social network factors. The approach is evaluated on two large real-world social rating datasets and shows improved performance over approaches that only use social network information.
An iac approach for detecting profile cloningIJNSA Journal
Nowadays, Online Social Networks (OSNs) are popular websites on the internet, which millions of users
register on and share their own personal information with others. Privacy threats and disclosing personal
information are the most important concerns of OSNs’ users. Recently, a new attack which is named
Identity Cloned Attack is detected on OSNs. In this attack the attacker tries to make a fake identity of a real
user in order to access to private information of the users’ friends which they do not publish on the public
profiles. In today OSNs, there are some verification services, but they are not active services and they are
useful for users who are familiar with online identity issues. In this paper, Identity cloned attacks are
explained in more details and a new and precise method to detect profile cloning in online social networks
is proposed. In this method, first, the social network is shown in a form of graph, then, according to
similarities among users, this graph is divided into smaller communities. Afterwards, all of the similar
profiles to the real profile are gathered (from the same community), then strength of relationship (among
all selected profiles and the real profile) is calculated, and those which have the less strength of
relationship will be verified by mutual friend system. In this study, in order to evaluate the effectiveness of
proposed method, all steps are applied on a dataset of Facebook, and finally this work is compared with
two previous works by applying them on the dataset.
International Journal of Engineering Research and DevelopmentIJERD Editor
Electrical, Electronics and Computer Engineering,
Information Engineering and Technology,
Mechanical, Industrial and Manufacturing Engineering,
Automation and Mechatronics Engineering,
Material and Chemical Engineering,
Civil and Architecture Engineering,
Biotechnology and Bio Engineering,
Environmental Engineering,
Petroleum and Mining Engineering,
Marine and Agriculture engineering,
Aerospace Engineering.
This document summarizes a research paper that presents a reputation system called Tulungan designed to measure contributor and rater reputation in collaborative web filtering systems. Tulungan aims to be resistant to slandering attacks, where malicious raters intentionally give inaccurate negative ratings. The paper describes Tulungan's algorithm, which initializes reputations and allows contributions, rating, and reputation computation in cycles. A simulation evaluates Tulungan in the presence of good, malicious, and slandering users, finding that Tulungan is effective even when good users are a minority and is resistant to slandering.
Social Networking Sites have become the means of the communication and have
experienced growth in the recent years. As these sites offer services for free of costs are
attracting the people all around the world. Some technologies are emerging in the field of
Internet but still the users are facing the security leakages by unauthorized users. Many of
the Social Sites are managed by the Third Party Domains which keep track of all the user
information along with the access details. Most Online Social Networking (OSN) Sites
provide an “accept all or nothing” mechanism for managing permission from Third Party
Access (TPA) to access user’s private data [3]. The Social Media sites do not provide any
mechanism for privacy on the shared data among the multiple users. Many users share their
personal information without knowing about the cyber thefts and risks associated with it.
From the survey it has been found that the teenagers are least concerned about the
navigating privacy. Privacy associated with the Social media is the very crucial thing.
Different methods are discussed regarding sharing of the personal information and leakage
of this information through different mediums. Different models are also proposed in this
paper regarding the privacy control of third party access of the personal information. An
approach is proposed which allows users to share their access control configuration for TPA
s with their friends who can reuse and rate such configurations [3]
1) The document discusses predicting the strength of ties between individuals in online social networks using measures of their ego network structures. It analyzes how factors like degree centrality, betweenness centrality, and dispersion within ego networks correlate with perceived tie strength.
2) An empirical study collected data on Facebook ego networks and tie strength perceptions from 41 respondents. Network measures like betweenness in ego networks were highly predictive of close ties.
3) The findings suggest that ego network analyses can reveal close friendships even without direct disclosure of that information, with implications for data privacy, understanding peer influence, and analyzing other networked data.
An Access Control Model for Collaborative Management of Shared Data in OSNSIJMER
This document presents a multi-party access control model for managing shared data in online social networks. It proposes that access control policies for shared data should be specified collaboratively by multiple associated users, not just the data owner. An access control policy format is defined that includes the controller, controller type, accessor, data specification, and authorization effect. A prototype application called MController is implemented that allows multiple users to specify access control policies and resolve conflicts for shared photos. An evaluation of MController found that users had a more positive view of its privacy controls compared to Facebook's default controls. Performance testing showed the policy evaluation mechanism scaled well as the number of controllers increased.
The document summarizes research issues, tools, and applications related to analyzing the blogosphere. It discusses how social networks form online through blogs and user-generated content. Various approaches are presented for modeling, analyzing, and mining the blogosphere to study influence, communities, and other phenomena. Tools and methods mentioned include network analysis, text mining, and simulating the blogosphere as a complex social network with nodes and relationships.
IRJET- Effective Countering of Communal Hatred During Disaster Events in Soci...IRJET Journal
This document summarizes a research paper that aims to effectively counter communal hatred during disaster events on social media. It uses machine learning techniques to analyze tweets and classify them based on parameters like offensive, hatred, or neither. Tweets are collected using Twitter's API and preprocessed. A supervised machine learning algorithm (Support Vector Machine) is trained on manually labeled tweet data to classify new tweets. The results are visualized in a pie chart graph displaying the percentage of tweets containing offensive, hatred, or neutral words. The goal is to reduce the spread of communal hate speech on social media during disasters.
This document discusses using trust and provenance for content filtering on the semantic web. It describes how trust can be inferred between individuals in social networks and how that trust information can be used to filter and recommend content. Applications mentioned include using trust ratings to help intelligence analysts sort through information by identifying reliable sources.
The document presents the technical design for a social networking site called AMBA. It aims to address security and privacy issues with current sites by reducing the availability of personal information. It will assign each user a unique PIN that must be shared to add friends or view profiles. Searching by name will not show results, only by PIN. The design includes user registration, login, profile creation, friend requests, and posting features. It will use a SQL Server database to store user data and Visual Studio for development. The high-level design seeks to make the site less "stalker friendly" while still enabling social connections.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
The document discusses how recommender systems are evolving with the rise of Web 2.0 and social media platforms. It outlines how these new platforms provide more user data like demographics, social connections, tags, and folksonomies that can be used to develop new and improved recommendation algorithms. Specifically, it discusses how trust between users and exploiting the social graph can help with challenges like cold starts and attacks. It also examines using tags for content-based and collaborative filtering recommendations. Overall, the integration of social media data and semantic approaches is leading to more personalized and higher quality recommendations.
My Privacy My decision: Control of Photo Sharing on Online Social NetworksIRJET Journal
This document summarizes a research paper that proposes a facial recognition system to help users control photo sharing on social networks while protecting privacy. It discusses how photo sharing on social networks can unintentionally reveal private user information through tags, comments or metadata. The proposed system would recognize faces in photos and allow users to choose privacy settings during the photo posting process. It would also use private user photos to train the facial recognition model while preserving privacy through a distributed consensus method. The goal is to give users more awareness and control over how their photos are shared and help prevent unintended disclosure of personal information.
IRJET- Fake Profile Identification using Machine LearningIRJET Journal
This document proposes a framework for identifying fake profiles on social media sites using machine learning. It involves selecting profile attributes from a dataset, training a random forest classifier model on 80% of the labeled real and fake profiles, and testing it on the remaining 20%. The random forest classifier is able to accurately classify profiles as real or fake with an efficiency of 95% based on attributes like number of friends, followers, and status updates. This automatic fake profile detection method could help social media sites manage the large volume of profiles that can't be manually reviewed.
IRJET- Tweet Segmentation and its Application to Named Entity RecognitionIRJET Journal
This document summarizes a research paper on tweet segmentation and its application to named entity recognition. It proposes a novel framework called Hybrid Segmentation that splits tweets into meaningful segments to preserve semantic context for downstream natural language processing applications like named entity recognition. HybridSeg finds optimal tweet segmentations by maximizing the stickiness score of segments, which considers global context based on English phrases and local context based on linguistic features or term dependencies within a batch of tweets. Experiments show significantly improved segmentation quality when learning both global and local contexts compared to global context alone. The segmented tweets can then be used for high accuracy named entity recognition through part-of-speech tagging.
This document discusses the selection and placement of various photographs in a magazine. It analyzes 6 different photos, describing where each would be placed and the reasons for choosing them. The reasons generally include liking the poses, costumes, framing, lighting, colors, composition and clarity of the images. Providing insight into the subjects and fitting nicely with the text or layout are also mentioned.
This document contains two short phrases: "38 group" and "Nino talabadze". It does not provide enough context or details to generate a meaningful multi-sentence summary. The document appears to list a group name and a person's name but without additional context around what they refer to or their significance.
This document summarizes a research paper that introduces a new class of complex-valued harmonic functions. The paper defines a generalized derivative operator for harmonic functions with varying arguments. It obtains a sufficient coefficient condition for functions to belong to the proposed class of starlike harmonic functions. It also shows that the coefficient condition is necessary for functions in the subclass of harmonic functions with varying arguments. The paper derives extreme points for functions in this subclass.
This document summarizes a research paper that proposes global block-based redundancy architectures for self-repairing of embedded memories. The key points are:
- Redundant rows and columns of memory are divided into blocks that can replace faulty blocks anywhere in the memory array, rather than just within the same row or column. This global approach helps repair clustered faults.
- A modified essential spare pivoting (MESP) algorithm is proposed for built-in redundancy analysis that has low area overhead. It collects faulty cell information and analyzes block-level faults.
- Simulation results show the proposed architectures and MESP algorithm significantly improve manufacturing yield, repair rates, and reliability compared to other approaches, due to their efficient
This document presents a general theory for NP-hard problems by developing a progressive model that classifies problems based on parameters similarly to how accounts are classified in a general ledger. It introduces 12 common NP-hard problems and develops governing equations to model the classification and solution behavior of the problems over time. The model aims to provide a unified framework and make predictions about NP-hard problems similarly to how a general ledger tracks financial inflows and outflows.
The document investigates cotton seed oil and neem methyl esters as biodiesel fuels in a CI engine. Cotton seed oil and neem oil were converted to methyl esters through a transesterification process. Various blends of the cotton seed and neem methyl esters with diesel were tested in a single cylinder diesel engine. Test results showed that the C20 blend, which is 20% cotton seed methyl ester and 80% diesel, had performance closest to diesel. Emissions and smoke were also lower for the biodiesel blends compared to pure diesel. Overall, the study found that cotton seed methyl ester provided better engine performance than neem methyl ester and that the C20 blend is a
Methodology used for improving overall equipment effectiveness by Implementi...IJMER
The global marketplace is highly competitive and organizations who want to survive long-term, have to continuously improve, change and adapt in response to market demands. Improvements in
a company's performance should focus on cost cutting, increasing productivity levels, quality and
guaranteeing deliveries in order to satisfy customers. Total Productive Maintenance (TPM) is one
method, which can be used to achieve these goals. TPM is an approach to equipment management that
involves employees from both production and maintenance departments. Its purpose is to eliminate major
production losses by introducing a program of continuous and systematic improvements to production
equipment.
A Special Type Of Differential Polynomial And Its Comparative Growth PropertiesIJMER
International Journal of Modern Engineering Research (IJMER) is Peer reviewed, online Journal. It serves as an international archival forum of scholarly research related to engineering and science education.
This document summarizes a study on the sintering mechanism of silica gel nanoparticles during initial heating stages. Thermogravimetric analysis showed weight loss up to 600°C attributed to removal of absorbed water and hydroxyl groups. Diffuse reflectance infrared spectroscopy revealed bonding changes - bridged hydroxyl groups were replaced by free hydroxyl and water molecules with heating. Heating also increased asymmetric stretching splitting, indicating greater long-range Coulombic forces from increased siloxane bonding between particles. The study concludes initial sintering is driven by dehydration and surface hydroxyl condensation forming siloxane bonds between particles.
Prospect of bioenergy substitution in tea industries of North East IndiaIJMER
Coal Straw
Thermal energy requirement (GJ/year) 12592 12592
Quantity required (tonnes/year) 3616 2610
Cost of fuel (Rs/tonne) 3500 1370
Total annual cost (Rs. Lakhs) 23.06 15.46
Savings (Rs. Lakhs) - 11.6
1) The document discusses the potential for substituting conventional fuels with bioenergy sources in tea processing industries in Northeast India to reduce costs and dependency on fossil fuels.
2) It analyzes the feasibility of biomass gasification, use of agricultural residues for process heating, and biodiesel production from non-ed
Web search engines help users find useful information on the WWW. However, when the same query is submitted by different users, typical search engines return the same result regardless of who submitted the query. Generally, each user has different information needs for his/her query. Therefore, the search results should be adapted to users with different information needs. So, there is need of
several approaches to adapting search results according to each user’s need for relevant information without any user effort. Such search systems that adapt to each user’s preferences can be achieved by constructing user profiles based on modified collaborative filtering with detailed analysis of user’s browsing history. There are three possible types of web search system which can provide personalized information: (1) systems using relevance feedback, (2) systems in which users register their interest, and (3) systems that recommend information based on user’s history. In first technique, users have to provide feedback on relevant or irrelevant judgments which is time consuming and the second one needs
registration of users with their static interests which need extra effort from user. So, the third technique is best in which users don’t have to give explicit rating; relevancy automatically tracked by user behavior with search results and history of data usage. It doesn’t require registration of interests; it captures changing interests of user dynamically by itself. The result section shows that user’s browsing history allows each user to perform more fine-grained search by capturing changes of each user’s
preferences without any user effort. Users need less time to find the relevant snippet in personalized
search results compared to original results.
This document summarizes a research paper that proposes a three-layered approach using particle swarm optimization (PSO) to improve the accuracy of clustering weather data.
The first layer partitions the dataset based on time series (e.g. seasons). Basic clustering algorithms like k-means are then applied in the second layer. In the third layer, PSO is used to refine the clusters by finding the best fitness function and evaluating how well data points fit existing clusters, in order to remove impurities from the dataset. The approach is tested on a weather dataset containing 10,000 instances spanning 1970-2010.
This document discusses integrating natural language processing and parse tree query language with text mining and topic summarization methods to more efficiently extract relevant content from documents. It presents an approach that uses natural language processing to automatically generate queries from sentences, and then applies a topic summarization method called TSCAN to identify themes, segment events, and construct an evolution graph to show relationships between events. The integrated system aims to make content extraction more effective and easier to use for real-time applications. Evaluation of the methods showed benefits for tasks like information extraction.
This document presents an experimental study on the parameters affecting the tribological performance of nano lubricant containing multi-walled carbon nanotubes (MWCNT) using design of experiments (DOE). Four factors were studied - MWCNT quantity, surfactant quantity, load, and speed. Experiments were conducted using a block and disk test setup to measure wear. The results showed that speed and MWCNT quantity had the greatest effect on wear, followed by surfactant quantity and load. The interaction between load and surfactant quantity and between load and MWCNT quantity were also significant. The study concluded that adding 0.05% MWCNT to the nano lubricant significantly reduced wear under different load and speed conditions
Influence of Skidded Distance on the Initial Velocity of Vehicle in Chain Acc...IJMER
International Journal of Modern Engineering Research (IJMER) is Peer reviewed, online Journal. It serves as an international archival forum of scholarly research related to engineering and science education.
A Review of FDM Based Parts to Act as Rapid ToolingIJMER
Fused Deposition Modeling (FDM) is one from basic Rapid Prototyping (RP) technologies
used in technical practice. In this contribution are presented basic information about parameters such
as layer thickness, part build orientation, raster angle, raster width and air gap. This study provides
insight into complex dependency of strength on process parameters. In this paper microphotographs
are used to show the mechanism of failure. The major reason for weak strength is attributed to
distortion within or between the layers.Developing a curved layer deposition methodology can
improve part quality by reduced lamination, reduction in the staircase effect which leads to improved
dimensional accuracy of the part. Less effort has been made to increase the range of FDM materials
to include metals or metal based composites with the help of metal based composite direct rapid
tooling will allow fabrication of injection moulding dies and inserts with desired thermal and
mechanical properties suitable for using directly in injection moulding machines for short term or
long term production runs
Impact of Mechanical System in Machining Of AISI 1018 Using Taguchi Design o...IJMER
The imperative objective of the science of metal cutting is the solution of practical problems
associated with the efficient and precise removal of metal from work piece. Optimization of process
parameters is done to have great control over quality, productivity and cost aspects of the process.
Taguchi method stresses the importance of studying the response variation using the signal–to–noise
(S/N) ratio, resulting in minimization of quality characteristic variation due to uncontrollable
parameter. Orthogonal array was adopted in order to planning the (L9) experimental runs in turning of
AISI 1018 by taking the help of software Minitab 16. The MRR and time
A Survey On Privacy Policy Inference for Social ImagesIRJET Journal
This document summarizes research on privacy issues related to sharing photos and content on social networks. It discusses how improved technology has led to increased privacy violations as users share large volumes of images with many people. The document reviews existing approaches to automating privacy settings for shared content, but notes that these may be insufficient for addressing unique privacy needs of images. It proposes generating user profiles and maintaining privacy inference policies based on user profiles, image content and metadata. The goal is to develop better systems to help users easily configure privacy settings for images shared on social networks.
Provide individualized suggestions
of data or products related to users’ needs
by Recommender systems (RSs). Even
if RSs have created substantial progresses
in theory and formula development and
have achieved many business successes, a
way to operate the wide accessible info in
online social Networks (OSNs) has been
mainly overlooked. Noticing such a gap in
the existing research in RSs and taking
into account a user’s choice being greatly
influenced by his/her trustworthy friends
and their opinions; this paper proposes a,
Fact Finder technique that improves the
prevailing recommendation approaches by
exploring a new source of data from
friends’ short posts in microbloggings as
micro-reviews.Degree of friends’
sentiment and level being sure to a user’s
choice are known by victimisation
machine learning strategies as well as
Naive Bayes, Logistic Regression and
Decision Trees. As the verification of the
proposed Fact finder, experiments
victimisation real social data from Twitter
microblogger area unit given and results
show the effectiveness and promising of
the planned approach.
Automatic Recommendation of Trustworthy Users in Online Product Rating SitesIRJET Journal
1) The document discusses methods for identifying trustworthy users and recommendations in online product rating sites. It notes that some recommendations may be misleading or harmful if they come from users with malicious intentions or lack competence.
2) It describes challenges with current recommendation systems, such as fake users corrupting ratings predictions and reducing accuracy. The goal is to identify and filter out untrustworthy recommendations to provide more accurate ratings and recommendations to users.
3) Several papers are reviewed that propose techniques like natural language processing of reviews, calculating reputation scores based on review criteria, and using interaction data and attributes to identify trustworthy friends in online communities. The objective is to develop robust methods for identifying trustworthy users and recommendations.
Spammer Detection and Fake User Identification on Social NetworksIRJET Journal
This document discusses methods for detecting spammers and fake users on social networks like Twitter. It provides a literature review of past research on spam detection techniques on Twitter. The techniques are categorized based on their ability to detect: (1) fake content, (2) spam based on URLs, (3) spam in popular topics, and (4) fake users. The techniques are also analyzed based on attributes like user attributes, content attributes, graph attributes, structural attributes, and time attributes. An implementation approach is proposed that involves collecting user data, employing machine learning algorithms like random forest for pattern recognition, using feature engineering, and integrating social media APIs for real-time monitoring. It also discusses integrating a user reporting mechanism to improve accuracy
IRJET- Personalised Privacy-Preserving Social Recommendation based on Ranking...IRJET Journal
This document proposes a framework called PrivRank that enables privacy-preserving social recommendations. PrivRank aims to protect users' private data from inference attacks while still allowing personalized ranking-based recommendations. It does this by obfuscating users' public data before publishing it to third parties. This allows third parties to provide accurate recommendations without accessing sensitive private user information. The framework is designed to efficiently provide continuous privacy protection for users' data streams over time as new data is published.
A Survey on Trust Inference Network for Personalized Use from Online Data RatingIRJET Journal
This document discusses a proposed new trust model called the "Web of Credit" (WoC) model for inferring personalized trust measures from online rating data in social networks. The WoC model constructs a trust network by tracking the flow of "credit" assigned from one user to another based on their ratings. It combines the objectiveness of reputation-based models which use rating histories, with the individualism of "Web of Trust" models which allow personalized trust measures. The document also presents the Core-Trust algorithm for inferring trust in this WoC-based network by considering factors like credit, risk, bias, and impedance derived from rating data. Experiments on real datasets showed the WoC model can infer trust more accurately than
This document discusses trust modeling approaches for social tagging systems. It describes existing problems with noisy and spam tags that make search inefficient. The proposed system models trust at three levels: spam content, tag-content associations, and spammers. Trust modeling is categorized into content and user trust modeling, ranging from simple to advanced approaches. User trust modeling, which assesses a user's reliability over time, is more popular than content trust modeling. The document outlines requirements and provides UML diagrams to illustrate the system.
IRJET-A Novel Technic to Notice Spam Reviews on e-ShoppingIRJET Journal
The document presents a novel technique for detecting spam reviews on e-commerce websites. It models review datasets as heterogeneous information networks and maps spam detection to a network classification problem. A weighting algorithm calculates the importance of each review feature. The proposed "Net Spam" framework improves spam detection accuracy compared to state-of-the-art methods while reducing time complexity by using higher-weighted features to identify spam reviews more efficiently. An evaluation on Amazon and Yelp review datasets found that modeling reviews and user behavior as networks achieved good performance in semi-supervised and unsupervised spam detection.
IRJET- Web User Trust Relationship Prediction based on Evidence TheoryIRJET Journal
1. The document proposes a method to predict trust relationships between web users based on evidence theory. It uses user ratings of web content as evidence to infer trust, with each rating treated as a piece of evidence.
2. The method computes personalized trust recommendations by analyzing the provenance of existing trust annotations in social networks. It then uses the computed trust values to personalize websites, like recommending movies based on trust.
3. The approach integrates trust, provenance, and annotations on the semantic web to process information. Two applications are presented that illustrate using trust annotations and provenance for personalization.
Predicting the Brand Popularity from the Brand MetadataIJECEIAES
The document presents a framework for predicting brand popularity from brand metadata on social networks. It identifies thoughtful comments from brand posts using natural language processing and classifies them as favorable or unfavorable. Brand metadata like numbers of likes, shares, and identified thoughtful comments are then combined to forecast future brand popularity. The performance of the proposed framework is evaluated against recent works in terms of thoughtful comment identification accuracy, execution time, popularity prediction accuracy, and prediction time. Results show improvements over existing approaches.
IRJET- Secure Social Network using Text MiningIRJET Journal
This document proposes a secure social network that uses text mining techniques. It discusses authenticating users with Aadhar numbers to allow only one account per user. It aims to restrict improper words and vulgar images/videos by maintaining dictionaries of abusive terms and notifying users about tagged inappropriate content. The proposed system focuses on privacy, restricting multiple accounts and abusive content through authentication, keyword detection, and notification processes to make user profiles and posts more secure.
This document discusses detecting spam comments on YouTube videos using machine learning techniques. It analyzes YouTube comments datasets using logistic regression, AdaBoost, decision trees and random forest algorithms. Neural networks achieved the highest accuracy of 91.65% for spam detection, an improvement of around 18% over existing approaches. The document outlines the methodology, including preprocessing, feature selection and extraction, and model building. It discusses the results and screenshots of a developed system for classifying YouTube comments as spam or not spam. In conclusion, machine learning techniques can effectively detect spam comments, though spammers may adapt over time to evade detection.
The size of the Internet enlarging as per to grow the users of search providers continually demand search
results that are accurate to their wishes. Personalized Search is one of the options available to users in
order to sculpt search results based on their personal data returned to them provided to the search
provider. This brings up fears of privacy issues however, as users are typically anxious to revealing
personal info to an often faceless service provider along the Internet. This work proposes to administer
with the privacy issues surrounding personalized search and discusses ways that privacy can be improved
so that users can get easier with the dismissal of their personal information in order to obtain more precise
search results.
This document discusses techniques for detecting fake news. It begins with an introduction to the problem of fake news and how it spreads on social media. It then reviews different machine learning techniques that have been used for fake news detection, including naïve bayes, decision trees, random forests, K-nearest neighbors, and LSTM. The document also categorizes different types of fake news and surveys related literature applying machine learning to fake news detection. It concludes that detecting fake news is still an ongoing challenge and more work is needed with improved datasets and models.
IRJET- Analysis on Existing Methodologies of User Service Rating Prediction S...IRJET Journal
This document summarizes and analyzes existing methodologies for user service rating prediction systems. It discusses recommendation systems including collaborative filtering, content-based filtering, and hybrid approaches. Collaborative filtering predicts user ratings based on opinions of other similar users but faces challenges of cold start, scalability, and sparsity. Content-based filtering relies on item profiles and user preferences to recommend similar items but requires detailed item information. Hybrid systems combine collaborative and content-based filtering to address their individual limitations. The document also examines social recommender systems and how they can account for relationship strength, expertise, and user similarity within social networks.
this is VTU FINAL YEAR PROJECT REPORT full report is attached below.this alone with front pages attached Front pages report follows all the guidelines specified by vtu according to our college.
IRJET - Socirank Identifying and Ranking Prevalent News Topics using Social M...IRJET Journal
1. The document proposes a framework called SociRank to identify and rank prevalent news topics using social media factors.
2. SociRank identifies topics prevalent in both social media and news media, and then ranks them based on their media focus in news, user attention in social media, and user interaction regarding the topic.
3. The experiments show that SociRank improves the quality and variety of automatically identified news topics compared to other topic identification and ranking methods.
A SECURED AUDITING PROTOCOL FOR TRANSFERRING DATA AND PROTECTED DISTRIBUTED S...IRJET Journal
This document proposes a secured auditing protocol for transferring data and protected distributed storage with social media. It discusses the limitations of existing systems for sharing data and photos on social networks, including privacy and security issues. The proposed system aims to address these issues through a new framework that uses encryption, anonymous profiles, integrity checks and user approval for data access and sharing. It describes the various modules of the new system like enrollment, account updating, file sharing, profile matching, and group management. The system is designed to allow secure data sharing while preserving user privacy through techniques like anonymous profiles and consent-based sharing.
AGGRESSION DETECTION USING MACHINE LEARNING MODELIRJET Journal
This document discusses a machine learning model to detect aggression on Twitter in real time. The proposed system extracts tweets using the Twitter API and uses the Flair model for feature extraction, training, prediction, and testing. The Flair model is updated incrementally when new labeled samples are received, achieving 93% accuracy, precision, and recall. The system can detect aggressive tweets in real time to help curb the spread of inappropriate online behavior. Future work includes expanding the approach to other social media platforms and monitoring individual users.
Similar to Social Tagging Of Multimedia Content A Model (20)
A Study on Translucent Concrete Product and Its Properties by Using Optical F...IJMER
- Translucent concrete is a concrete based material with light-transferring properties,
obtained due to embedded light optical elements like Optical fibers used in concrete. Light is conducted
through the concrete from one end to the other. This results into a certain light pattern on the other
surface, depending on the fiber structure. Optical fibers transmit light so effectively that there is
virtually no loss of light conducted through the fibers. This paper deals with the modeling of such
translucent or transparent concrete blocks and panel and their usage and also the advantages it brings
in the field. The main purpose is to use sunlight as a light source to reduce the power consumption of
illumination and to use the optical fiber to sense the stress of structures and also use this concrete as an
architectural purpose of the building
Developing Cost Effective Automation for Cotton Seed DelintingIJMER
A low cost automation system for removal of lint from cottonseed is to be designed and
developed. The setup consists of stainless steel drum with stirrer in which cottonseeds having lint is mixed
with concentrated sulphuric acid. So lint will get burn. This lint free cottonseed treated with lime water to
neutralize acidic nature. After water washing this cottonseeds are used for agriculter purpose
Study & Testing Of Bio-Composite Material Based On Munja FibreIJMER
The incorporation of natural fibres such as munja fiber composites has gained
increasing applications both in many areas of Engineering and Technology. The aim of this study is to
evaluate mechanical properties such as flexural and tensile properties of reinforced epoxy composites.
This is mainly due to their applicable benefits as they are light weight and offer low cost compared to
synthetic fibre composites. Munja fibres recently have been a substitute material in many weight-critical
applications in areas such as aerospace, automotive and other high demanding industrial sectors. In
this study, natural munja fibre composites and munja/fibreglass hybrid composites were fabricated by a
combination of hand lay-up and cold-press methods. A new variety in munja fibre is the present work
the main aim of the work is to extract the neat fibre and is characterized for its flexural characteristics.
The composites are fabricated by reinforcing untreated and treated fibre and are tested for their
mechanical, properties strictly as per ASTM procedures.
Hybrid Engine (Stirling Engine + IC Engine + Electric Motor)IJMER
Hybrid engine is a combination of Stirling engine, IC engine and Electric motor. All these 3 are
connected together to a single shaft. The power source of the Stirling engine will be a Solar Panel. The aim of
this is to run the automobile using a Hybrid engine
Fabrication & Characterization of Bio Composite Materials Based On Sunnhemp F...IJMER
This document summarizes research on the fabrication and characterization of bio-composite materials using sunnhemp fibre. The document discusses how sunnhemp fibre was used to reinforce an epoxy matrix through hand lay-up methods. Various mechanical properties of the bio-composites were tested, including tensile, flexural, and impact properties. The results of the mechanical tests on the bio-composite specimens are presented. Potential applications of the sunnhemp fibre bio-composites are also suggested, such as in fall ceilings, partitions, packaging, automotive interiors, and toys.
Geochemistry and Genesis of Kammatturu Iron Ores of Devagiri Formation, Sandu...IJMER
The Greenstone belts of Karnataka are enriched in BIFs in Dharwar craton, where Iron
formations are confined to the basin shelf, clearly separated from the deeper-water iron formation that
accumulated at the basin margin and flanking the marine basin. Geochemical data procured in terms of
major, trace and REE are plotted in various diagrams to interpret the genesis of BIFs. Al2O3, Fe2O3 (T),
TiO2, CaO, and SiO2 abundances and ratios show a wide variation. Ni, Co, Zr, Sc, V, Rb, Sr, U, Th,
ΣREE, La, Ce and Eu anomalies and their binary relationships indicate that wherever the terrigenous
component has increased, the concentration of elements of felsic such as Zr and Hf has gone up. Elevated
concentrations of Ni, Co and Sc are contributed by chlorite and other components characteristic of basic
volcanic debris. The data suggest that these formations were generated by chemical and clastic
sedimentary processes on a shallow shelf. During transgression, chemical precipitation took place at the
sediment-water interface, whereas at the time of regression. Iron ore formed with sedimentary structures
and textures in Kammatturu area, in a setting where the water column was oxygenated.
Experimental Investigation on Characteristic Study of the Carbon Steel C45 in...IJMER
In this paper, the mechanical characteristics of C45 medium carbon steel are investigated
under various working conditions. The main characteristic to be studied on this paper is impact toughness
of the material with different configurations and the experiment were carried out on charpy impact testing
equipment. This study reveals the ability of the material to absorb energy up to failure for various
specimen configurations under different heat treated conditions and the corresponding results were
compared with the analysis outcome
Non linear analysis of Robot Gun Support Structure using Equivalent Dynamic A...IJMER
Robot guns are being increasingly employed in automotive manufacturing to replace
risky jobs and also to increase productivity. Using a single robot for a single operation proves to be
expensive. Hence for cost optimization, multiple guns are mounted on a single robot and multiple
operations are performed. Robot Gun structure is an efficient way in which multiple welds can be done
simultaneously. However mounting several weld guns on a single structure induces a variety of
dynamic loads, especially during movement of the robot arm as it maneuvers to reach the weld
locations. The primary idea employed in this paper, is to model those dynamic loads as equivalent G
force loads in FEA. This approach will be on the conservative side, and will be saving time and
subsequently cost efficient. The approach of the paper is towards creating a standard operating
procedure when it comes to analysis of such structures, with emphasis on deploying various technical
aspects of FEA such as Non Linear Geometry, Multipoint Constraint Contact Algorithm, Multizone
meshing .
Static Analysis of Go-Kart Chassis by Analytical and Solid Works SimulationIJMER
This paper aims to do modelling, simulation and performing the static analysis of a go
kart chassis consisting of Circular beams. Modelling, simulations and analysis are performed using 3-D
modelling software i.e. Solid Works and ANSYS according to the rulebook provided by Indian Society of
New Era Engineers (ISNEE) for National Go Kart Championship (NGKC-14).The maximum deflection is
determined by performing static analysis. Computed results are then compared to analytical calculation,
where it is found that the location of maximum deflection agrees well with theoretical approximation but
varies on magnitude aspect.
In récent year various vehicle introduced in market but due to limitation in
carbon émission and BS Séries limitd speed availability vehicle in the market and causing of
environnent pollution over few year There is need to decrease dependancy on fuel vehicle.
bicycle is to be modified for optional in the future To implement new technique using change in
pedal assembly and variable speed gearbox such as planetary gear optimise speed of vehicle
with variable speed ratio.To increase the efficiency of bicycle for confortable drive and to
reduce torque appli éd on bicycle. we introduced epicyclic gear box in which transmission done
throgh Chain Drive (i.e. Sprocket )to rear wheel with help of Epicyclical gear Box to give
number of différent Speed during driving.To reduce torque requirent in the cycle with change in
the pedal mechanism
Integration of Struts & Spring & Hibernate for Enterprise ApplicationsIJMER
This document discusses integrating the Spring, Struts, and Hibernate frameworks to develop enterprise applications. It provides an overview of each framework and their features. The Spring Framework is a lightweight, modular framework that allows for inversion of control and aspect-oriented programming. It can be used to develop any or all tiers of an application. The document proposes an architecture for an e-commerce website that integrates these three frameworks, with Spring handling the business layer, Struts the presentation layer, and Hibernate the data access layer. This modular approach allows for clear separation of concerns and reduces complexity in application development.
Microcontroller Based Automatic Sprinkler Irrigation SystemIJMER
Microcontroller based Automatic Sprinkler System is a new concept of using
intelligence power of embedded technology in the sprinkler irrigation work. Designed system replaces
the conventional manual work involved in sprinkler irrigation to automatic process. Using this system a
farmer is protected against adverse inhuman weather conditions, tedious work of changing over of
sprinkler water pipe lines & risk of accident due to high pressure in the water pipe line. Overall
sprinkler irrigation work is transformed in to a comfortableautomatic work. This system provides
flexibility & accuracy in respect of time set for the operation of a sprinkler water pipe lines. In present
work the author has designed and developed an automatic sprinkler irrigation system which is
controlled and monitored by a microcontroller interfaced with solenoid valves.
On some locally closed sets and spaces in Ideal Topological SpacesIJMER
This document introduces and studies the concept of δˆ s-locally closed sets in ideal topological spaces. Some key points:
- A subset A is δˆ s-locally closed if A can be written as the intersection of a δˆ s-open set and a δˆ s-closed set.
- Various properties of δˆ s-locally closed sets are introduced and characterized, including relationships to other concepts like generalized locally closed sets.
- It is shown that a subset A is δˆ s-locally closed if and only if A can be written as the intersection of a δˆ s-open set and the δˆ s-closure of A.
- Theore
Intrusion Detection and Forensics based on decision tree and Association rule...IJMER
This paper present an approach based on the combination of, two techniques using
decision tree and Association rule mining for Probe attack detection. This approach proves to be
better than the traditional approach of generating rules for fuzzy expert system by clustering methods.
Association rule mining for selecting the best attributes together and decision tree for identifying the
best parameters together to create the rules for fuzzy expert system. After that rules for fuzzy expert
system are generated using association rule mining and decision trees. Decision trees is generated for
dataset and to find the basic parameters for creating the membership functions of fuzzy inference
system. Membership functions are generated for the probe attack. Based on these rules we have
created the fuzzy inference system that is used as an input to neuro-fuzzy system. Fuzzy inference
system is loaded to neuro-fuzzy toolbox as an input and the final ANFIS structure is generated for
outcome of neuro-fuzzy approach. The experiments and evaluations of the proposed method were
done with NSL-KDD intrusion detection dataset. As the experimental results, the proposed approach
based on the combination of, two techniques using decision tree and Association rule mining
efficiently detected probe attacks. Experimental results shows better results for detecting intrusions as
compared to others existing methods
Natural Language Ambiguity and its Effect on Machine LearningIJMER
This document discusses natural language ambiguity and its effect on machine learning. It begins by introducing different types of ambiguity that exist in natural languages, including lexical, syntactic, semantic, discourse, and pragmatic ambiguities. It then examines how these ambiguities present challenges for computational linguistics and machine translation systems. Specifically, it notes that ambiguity is a major problem for computers in processing human language as they lack the world knowledge and context that humans use to resolve ambiguities. The document concludes by outlining the typical process of machine translation and how ambiguities can interfere with tasks like analysis, transfer, and generation of text in the target language.
Today in era of software industry there is no perfect software framework available for
analysis and software development. Currently there are enormous number of software development
process exists which can be implemented to stabilize the process of developing a software system. But no
perfect system is recognized till yet which can help software developers for opting of best software
development process. This paper present the framework of skillful system combined with Likert scale. With
the help of Likert scale we define a rule based model and delegate some mass score to every process and
develop one tool name as MuxSet which will help the software developers to select an appropriate
development process that may enhance the probability of system success.
Material Parameter and Effect of Thermal Load on Functionally Graded CylindersIJMER
The present study investigates the creep in a thick-walled composite cylinders made
up of aluminum/aluminum alloy matrix and reinforced with silicon carbide particles. The distribution
of SiCp is assumed to be either uniform or decreasing linearly from the inner to the outer radius of
the cylinder. The creep behavior of the cylinder has been described by threshold stress based creep
law with a stress exponent of 5. The composite cylinders are subjected to internal pressure which is
applied gradually and steady state condition of stress is assumed. The creep parameters required to
be used in creep law, are extracted by conducting regression analysis on the available experimental
results. The mathematical models have been developed to describe steady state creep in the composite
cylinder by using von-Mises criterion. Regression analysis is used to obtain the creep parameters
required in the study. The basic equilibrium equation of the cylinder and other constitutive equations
have been solved to obtain creep stresses in the cylinder. The effect of varying particle size, particle
content and temperature on the stresses in the composite cylinder has been analyzed. The study
revealed that the stress distributions in the cylinder do not vary significantly for various combinations
of particle size, particle content and operating temperature except for slight variation observed for
varying particle content. Functionally Graded Materials (FGMs) emerged and led to the development
of superior heat resistant materials.
Energy Audit is the systematic process for finding out the energy conservation
opportunities in industrial processes. The project carried out studies on various energy conservation
measures application in areas like lighting, motors, compressors, transformer, ventilation system etc.
In this investigation, studied the technical aspects of the various measures along with its cost benefit
analysis.
Investigation found that major areas of energy conservation are-
1. Energy efficient lighting schemes.
2. Use of electronic ballast instead of copper ballast.
3. Use of wind ventilators for ventilation.
4. Use of VFD for compressor.
5. Transparent roofing sheets to reduce energy consumption.
So Energy Audit is the only perfect & analyzed way of meeting the Industrial Energy Conservation.
An Implementation of I2C Slave Interface using Verilog HDLIJMER
This document describes the implementation of an I2C slave interface using Verilog HDL. It introduces the I2C protocol which uses only two bidirectional lines (SDA and SCL) for communication. The document discusses the I2C protocol specifications including start/stop conditions, addressing, read/write operations, and acknowledgements. It then provides details on designing an I2C slave module in Verilog that responds to commands from an I2C master and allows synchronization through clock stretching. The module is simulated in ModelSim and synthesized in Xilinx. Simulation waveforms demonstrate successful read and write operations to the slave device.
Discrete Model of Two Predators competing for One PreyIJMER
This paper investigates the dynamical behavior of a discrete model of one prey two
predator systems. The equilibrium points and their stability are analyzed. Time series plots are obtained
for different sets of parameter values. Also bifurcation diagrams are plotted to show dynamical behavior
of the system in selected range of growth parameter
Main news related to the CCS TSI 2023 (2023/1695)Jakub Marek
An English 🇬🇧 translation of a presentation to the speech I gave about the main changes brought by CCS TSI 2023 at the biggest Czech conference on Communications and signalling systems on Railways, which was held in Clarion Hotel Olomouc from 7th to 9th November 2023 (konferenceszt.cz). Attended by around 500 participants and 200 on-line followers.
The original Czech 🇨🇿 version of the presentation can be found here: https://www.slideshare.net/slideshow/hlavni-novinky-souvisejici-s-ccs-tsi-2023-2023-1695/269688092 .
The videorecording (in Czech) from the presentation is available here: https://youtu.be/WzjJWm4IyPk?si=SImb06tuXGb30BEH .
"$10 thousand per minute of downtime: architecture, queues, streaming and fin...Fwdays
Direct losses from downtime in 1 minute = $5-$10 thousand dollars. Reputation is priceless.
As part of the talk, we will consider the architectural strategies necessary for the development of highly loaded fintech solutions. We will focus on using queues and streaming to efficiently work and manage large amounts of data in real-time and to minimize latency.
We will focus special attention on the architectural patterns used in the design of the fintech system, microservices and event-driven architecture, which ensure scalability, fault tolerance, and consistency of the entire system.
From Natural Language to Structured Solr Queries using LLMsSease
This talk draws on experimentation to enable AI applications with Solr. One important use case is to use AI for better accessibility and discoverability of the data: while User eXperience techniques, lexical search improvements, and data harmonization can take organizations to a good level of accessibility, a structural (or “cognitive” gap) remains between the data user needs and the data producer constraints.
That is where AI – and most importantly, Natural Language Processing and Large Language Model techniques – could make a difference. This natural language, conversational engine could facilitate access and usage of the data leveraging the semantics of any data source.
The objective of the presentation is to propose a technical approach and a way forward to achieve this goal.
The key concept is to enable users to express their search queries in natural language, which the LLM then enriches, interprets, and translates into structured queries based on the Solr index’s metadata.
This approach leverages the LLM’s ability to understand the nuances of natural language and the structure of documents within Apache Solr.
The LLM acts as an intermediary agent, offering a transparent experience to users automatically and potentially uncovering relevant documents that conventional search methods might overlook. The presentation will include the results of this experimental work, lessons learned, best practices, and the scope of future work that should improve the approach and make it production-ready.
ScyllaDB is making a major architecture shift. We’re moving from vNode replication to tablets – fragments of tables that are distributed independently, enabling dynamic data distribution and extreme elasticity. In this keynote, ScyllaDB co-founder and CTO Avi Kivity explains the reason for this shift, provides a look at the implementation and roadmap, and shares how this shift benefits ScyllaDB users.
"Scaling RAG Applications to serve millions of users", Kevin GoedeckeFwdays
How we managed to grow and scale a RAG application from zero to thousands of users in 7 months. Lessons from technical challenges around managing high load for LLMs, RAGs and Vector databases.
In the realm of cybersecurity, offensive security practices act as a critical shield. By simulating real-world attacks in a controlled environment, these techniques expose vulnerabilities before malicious actors can exploit them. This proactive approach allows manufacturers to identify and fix weaknesses, significantly enhancing system security.
This presentation delves into the development of a system designed to mimic Galileo's Open Service signal using software-defined radio (SDR) technology. We'll begin with a foundational overview of both Global Navigation Satellite Systems (GNSS) and the intricacies of digital signal processing.
The presentation culminates in a live demonstration. We'll showcase the manipulation of Galileo's Open Service pilot signal, simulating an attack on various software and hardware systems. This practical demonstration serves to highlight the potential consequences of unaddressed vulnerabilities, emphasizing the importance of offensive security practices in safeguarding critical infrastructure.
High performance Serverless Java on AWS- GoTo Amsterdam 2024Vadym Kazulkin
Java is for many years one of the most popular programming languages, but it used to have hard times in the Serverless community. Java is known for its high cold start times and high memory footprint, comparing to other programming languages like Node.js and Python. In this talk I'll look at the general best practices and techniques we can use to decrease memory consumption, cold start times for Java Serverless development on AWS including GraalVM (Native Image) and AWS own offering SnapStart based on Firecracker microVM snapshot and restore and CRaC (Coordinated Restore at Checkpoint) runtime hooks. I'll also provide a lot of benchmarking on Lambda functions trying out various deployment package sizes, Lambda memory settings, Java compilation options and HTTP (a)synchronous clients and measure their impact on cold and warm start times.
"Choosing proper type of scaling", Olena SyrotaFwdays
Imagine an IoT processing system that is already quite mature and production-ready and for which client coverage is growing and scaling and performance aspects are life and death questions. The system has Redis, MongoDB, and stream processing based on ksqldb. In this talk, firstly, we will analyze scaling approaches and then select the proper ones for our system.
What is an RPA CoE? Session 2 – CoE RolesDianaGray10
In this session, we will review the players involved in the CoE and how each role impacts opportunities.
Topics covered:
• What roles are essential?
• What place in the automation journey does each role play?
Speaker:
Chris Bolin, Senior Intelligent Automation Architect Anika Systems
Freshworks Rethinks NoSQL for Rapid Scaling & Cost-EfficiencyScyllaDB
Freshworks creates AI-boosted business software that helps employees work more efficiently and effectively. Managing data across multiple RDBMS and NoSQL databases was already a challenge at their current scale. To prepare for 10X growth, they knew it was time to rethink their database strategy. Learn how they architected a solution that would simplify scaling while keeping costs under control.
What is an RPA CoE? Session 1 – CoE VisionDianaGray10
In the first session, we will review the organization's vision and how this has an impact on the COE Structure.
Topics covered:
• The role of a steering committee
• How do the organization’s priorities determine CoE Structure?
Speaker:
Chris Bolin, Senior Intelligent Automation Architect Anika Systems
inQuba Webinar Mastering Customer Journey Management with Dr Graham HillLizaNolte
HERE IS YOUR WEBINAR CONTENT! 'Mastering Customer Journey Management with Dr. Graham Hill'. We hope you find the webinar recording both insightful and enjoyable.
In this webinar, we explored essential aspects of Customer Journey Management and personalization. Here’s a summary of the key insights and topics discussed:
Key Takeaways:
Understanding the Customer Journey: Dr. Hill emphasized the importance of mapping and understanding the complete customer journey to identify touchpoints and opportunities for improvement.
Personalization Strategies: We discussed how to leverage data and insights to create personalized experiences that resonate with customers.
Technology Integration: Insights were shared on how inQuba’s advanced technology can streamline customer interactions and drive operational efficiency.
"NATO Hackathon Winner: AI-Powered Drug Search", Taras KlobaFwdays
This is a session that details how PostgreSQL's features and Azure AI Services can be effectively used to significantly enhance the search functionality in any application.
In this session, we'll share insights on how we used PostgreSQL to facilitate precise searches across multiple fields in our mobile application. The techniques include using LIKE and ILIKE operators and integrating a trigram-based search to handle potential misspellings, thereby increasing the search accuracy.
We'll also discuss how the azure_ai extension on PostgreSQL databases in Azure and Azure AI Services were utilized to create vectors from user input, a feature beneficial when users wish to find specific items based on text prompts. While our application's case study involves a drug search, the techniques and principles shared in this session can be adapted to improve search functionality in a wide range of applications. Join us to learn how PostgreSQL and Azure AI can be harnessed to enhance your application's search capability.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/temporal-event-neural-networks-a-more-efficient-alternative-to-the-transformer-a-presentation-from-brainchip/
Chris Jones, Director of Product Management at BrainChip , presents the “Temporal Event Neural Networks: A More Efficient Alternative to the Transformer” tutorial at the May 2024 Embedded Vision Summit.
The expansion of AI services necessitates enhanced computational capabilities on edge devices. Temporal Event Neural Networks (TENNs), developed by BrainChip, represent a novel and highly efficient state-space network. TENNs demonstrate exceptional proficiency in handling multi-dimensional streaming data, facilitating advancements in object detection, action recognition, speech enhancement and language model/sequence generation. Through the utilization of polynomial-based continuous convolutions, TENNs streamline models, expedite training processes and significantly diminish memory requirements, achieving notable reductions of up to 50x in parameters and 5,000x in energy consumption compared to prevailing methodologies like transformers.
Integration with BrainChip’s Akida neuromorphic hardware IP further enhances TENNs’ capabilities, enabling the realization of highly capable, portable and passively cooled edge devices. This presentation delves into the technical innovations underlying TENNs, presents real-world benchmarks, and elucidates how this cutting-edge approach is positioned to revolutionize edge AI across diverse applications.
Must Know Postgres Extension for DBA and Developer during MigrationMydbops
Mydbops Opensource Database Meetup 16
Topic: Must-Know PostgreSQL Extensions for Developers and DBAs During Migration
Speaker: Deepak Mahto, Founder of DataCloudGaze Consulting
Date & Time: 8th June | 10 AM - 1 PM IST
Venue: Bangalore International Centre, Bangalore
Abstract: Discover how PostgreSQL extensions can be your secret weapon! This talk explores how key extensions enhance database capabilities and streamline the migration process for users moving from other relational databases like Oracle.
Key Takeaways:
* Learn about crucial extensions like oracle_fdw, pgtt, and pg_audit that ease migration complexities.
* Gain valuable strategies for implementing these extensions in PostgreSQL to achieve license freedom.
* Discover how these key extensions can empower both developers and DBAs during the migration process.
* Don't miss this chance to gain practical knowledge from an industry expert and stay updated on the latest open-source database trends.
Mydbops Managed Services specializes in taking the pain out of database management while optimizing performance. Since 2015, we have been providing top-notch support and assistance for the top three open-source databases: MySQL, MongoDB, and PostgreSQL.
Our team offers a wide range of services, including assistance, support, consulting, 24/7 operations, and expertise in all relevant technologies. We help organizations improve their database's performance, scalability, efficiency, and availability.
Contact us: info@mydbops.com
Visit: https://www.mydbops.com/
Follow us on LinkedIn: https://in.linkedin.com/company/mydbops
For more details and updates, please follow up the below links.
Meetup Page : https://www.meetup.com/mydbops-databa...
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The Microsoft 365 Migration Tutorial For Beginner.pptxoperationspcvita
This presentation will help you understand the power of Microsoft 365. However, we have mentioned every productivity app included in Office 365. Additionally, we have suggested the migration situation related to Office 365 and how we can help you.
You can also read: https://www.systoolsgroup.com/updates/office-365-tenant-to-tenant-migration-step-by-step-complete-guide/
The Microsoft 365 Migration Tutorial For Beginner.pptx
Social Tagging Of Multimedia Content A Model
1. www.ijmer.com
International Journal of Modern Engineering Research (IJMER)
Vol. 3, Issue. 5, Sep - Oct. 2013 pp-2920-2923
ISSN: 2249-6645
Social Tagging Of Multimedia Content A Model
Abdul Rabbani1, P. U.V. Pavan Kumar2, Dr. Md. Ali Hussain3
1
M.Tech, Dept. of ECE, Sri Sunflower College of Engineering & Technology, A.P., India.
Asst.Professor, Dept. of ECE, Sri Sunflower College of Engineering & Technology, A.P., India.
3
Professor, Dept. of Electronics and Computer Engineering, KL University, Guntur, A.P., India.
2
ABSTRACT: Social networks are very popular now days, as it facilitates search and retrieval of multimedia features.
Anyway, noisy and spam annotations often make it difficult to perform an efficient search. Users may make mistakes in
tagging and irrelevant tags and content may be maliciously added for advertisement or self-promotion. This article examine
recent advances in techniques for combating such noise and spam in social tagging. The trust relationship among users has a
direct impact on the sharing and transmission mode of digital contents. To effectively assess direct or recommended trust
between users, this paper proposed a multimedia social networks trust model based on small world theory. Online and
Internet databases and early websites deployed them as a way for publishers to help users find content.
Keywords: Spam, Multimedia Social Networks, Websites.
I.
INTRODUCTION
When information is exchanged on the Internet, malicious individuals are everywhere, trying to take advantage of
the information exchange structure for their own benefit, while bothering and spamming others. Before social tagging
became popular, spam content was observed in various domains: first in e-mail, and then in Web search networks have been
also influenced by malicious peers, and thus various solutions based on trust and reputation have been proposed, which dealt
with collecting information on peer behavior, scoring and ranking peers, and responding based on the scores . Today, even
blogs are spammed. Ratings in online reputation systems, such as eBay, Amazon, and Epinions, are very similar to tagging
systems and they may face the problem of unfair ratings by artificially inflating or deflating reputations. Several filtering
techniques for excluding unfair ratings are proposed in the literature. Unfortunately, the countermeasures developed for email and Web spam do not directly apply to social networks.
II.
BACKGROUND
Social networks and multimedia content sharing Web sites have become increasingly popular in recent years. Their
service typically focuses on building online communities of people who share interests and activities, or are interested in
exploring the interests and activities of others. At the same time, they have become a popular way to share and disseminate
information. For
Example, users upload their personal photos and share them through online communities, letting other people comment or
rate them.
One important challenge in tagging is to identify the most appropriate tags for given content, and at the same time,
to eliminate noisy or spam tags. The shared content is sometimes assigned with inappropriate tags for several reasons. First
of all, users are human beings and may commit mistakes. Moreover, it is possible to provide wrong tags on purpose for
advertisement, self-promotion, or to increase the rank of a particular tag in automatic search engines. Consequently,
assigning free-form keywords (tags) to multimedia content has a risk that wrong or irrelevant tags eventually prevent users
from the benefits of annotated content.
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International Journal of Modern Engineering Research (IJMER)
Vol. 3, Issue. 5, Sep - Oct. 2013 pp-2920-2923
ISSN: 2249-6645
III.
TRUST MODELING
The social network approach to design large-scale systems has significant benefits including scalability, low cost of
ownership, robustness, and ability to provide site autonomy. However, this approach has several drawbacks as well including
trust issues and lack of coordination and control among the peers. We present a trust model for a social network structured
large-scale network computing system and completely define the trust model and describe the schemes used in it. Central to
the model is the idea of maintaining a recommender network that can be used to obtain references about a target domain.
Simulation results indicate that the trust model is capable of building and maintaining trust and also identifying the bad
domains. In a social tagging system, spam or noise can be injected at three different levels: spam content, spam tag-content
association, and spammer. Trust modeling can be performed at each level separately or different levels can be considered
jointly to produce trust models, for example, to assess a user’s reliability, one can consider not only the user profile, but also
the content that the user uploaded to a social system. In this article, we categorize trust modeling approaches into two classes
according to the target of trust, i.e., user and content trust modeling. Presented approaches are sorted based on their
complexity from simple to advanced, separately for both content and user trust models.
IV.
CONTENT TRUST MODELING
Approaches for content trust modeling utilize features extracted from content information, users profiles and/or
associated tags to detect specific spam content. Trust Rank relies on an important empirical observation called approximate
isolation of the good set: good pages seldom point to bad ones. It starts from a set of seeds selected as highly qualified,
credible and popular Web pages in the Web graph, and then iteratively propagates trust scores to all nodes in the graph by
splitting the trust score of a node among its neighbors according to a weighting scheme. Trust Rank effectively removes
most of the spam from the top-scored Web pages however it is unable to effectively separate low-scored good sites from bad
ones, due to the lack of distinguishing features.
Content trust modeling is used to classify content (e.g., Web pages, images, and videos) as spam or legitimate. In
this case, the target of trust is content (resource), and thus a trust score is given to each content based on its content and/or
associated tags. Content trust models reduce the prominence of content likely to be spam, usually in query-based retrieval
results. They try to provide better ordering of the results to reduce the exposure of the spam to users. The administrator can
go a step further and remove all content contributed by the user who posted the incorrect content.
V.
USER TRUST MODELING
The aforementioned studies consider users’ reliability as static at a specific moment. However, a user’s trust in a
social tagging system is dynamic, i.e., it changes over time. The tagging history of a user is better to consider, because a
consistent good behavior of a user in the past can suddenly change by a few mistakes, which consequently ruins his/her trust
in tagging.
In user trust modeling, trust is given to each user based on the information extracted from a user’s account, his/her
interaction with other participants within the social network, and/or the relationship between the content and tags that the
user contributed to the social tagging system. Given a user trust score, the user might be flagged as a legitimate user or
spammer
5.1 EVALUATION
Data sets used for development and evaluation of trust modeling techniques have a wide range of diversity in terms
of content, numbers of resources, tags and users, and type of spam. Some researchers dealing with bookmarks used a public
data set released by BibSonomy as a part of the ECML PKDD Discovery Challenge 2008 on Spam Detection in Social
Bookmarking Systems.
To model trust in other types of tagging systems, where spam is introduced through videos, tweets, or user profiles,
data are usually crawled from the corresponding social network, like YouTube, Twitter, or MySpace, respectively. For
example, Lee et al. [28] collected around 215,000 users and 4 million tweets from Twitter. Since this raw data are missing
ground truth for evaluation, they manually labeled a small portion of users distinguishing between legitimate users,
To model trust in other types of tagging systems, where spam is introduced through videos, tweets, or user profiles, data are
usually crawled from the corresponding social network, like YouTube, Twitter, or MySpace, respectively Since this raw data
are missing ground truth for evaluation, they manually labeled a small portion of users distinguishing between legitimate
users,
5.2 ALGORITHM
Trust modeling can be formulated as either a classification problem or a ranking problem, depending on the way of
treatment. In the classification problem, the results of an algorithm can be summarized by a confusion matrix from groundwww.ijmer.com
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3. International Journal of Modern Engineering Research (IJMER)
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Vol. 3, Issue. 5, Sep - Oct. 2013 pp-2920-2923
ISSN: 2249-6645
truth data and predicted labels, which contains the number of true positives, true negatives, false positives, and false
negatives. From these values, classical
measures such as a receiver operating characteristic (ROC), the area under the ROC curve (AUC), precision-recall (PR)
curves, and F-measure can be derived.
VI.
EXPERIMENTAL RESULTS
User profile
Image upload page
Image search page
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International Journal of Modern Engineering Research (IJMER)
Vol. 3, Issue. 5, Sep - Oct. 2013 pp-2920-2923
ISSN: 2249-6645
VII.
CONCLUSION AND FUTURE RESEARCH
In this article, we dealt with one of the key issues in social tagging systems: combating noise and spam. We
classified existing studies in the literature into two categories, i.e., content and user trust modeling. Representative
techniques in each category were analyzed and compared. In addition, existing databases and evaluation protocols were re
viewed. An example system was presented to demonstrate how trust modeling can be particularly employed in a popular
application of image sharing and geotagging. Finally, open issues and future research trends were prospected. As online
social networks and content sharing services evolve rapidly, we believe that the research on enhancing reliability and
trustworthiness of such services will become increasingly important
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