The document proposes an Incremental Short Text Summarization (IncreSTS) algorithm to generate summaries of comment streams on social media in real-time. IncreSTS models the problem as incremental clustering and can update clustering results with new comments. It identifies top-k clusters of comments expressing different opinions. For each cluster, key terms are extracted to create a visual summary cloud allowing users to easily understand the main points without reading all comments. The algorithm is efficient, scalable, and can handle outliers to meet the real-time needs of social media comment stream summarization.
Towards Real-Time Summarization of Scheduled Events from Twitter StreamsDamiano Spina
This work explores the real-time summarization of sched-
uled events such as soccer games from torrential
ows of Twitter streams. We propose and evaluate an approach
that substantially shrinks the stream of tweets in real-time,
and consists of two steps: (i) sub-event detection, which
determines if something new has occurred, and (ii) tweet se-
lection, which picks a representative tweet to describe each sub-event. We compare the summaries generated in three
languages for all the soccer games in Copa America 2011
to reference live reports oered by Yahoo! Sports journal-
ists. We show that simple text analysis methods which do
not involve external knowledge lead to summaries that cover
84% of the sub-events on average, and 100% of key types of sub-events (such as goals in soccer). Our approach should
be straightforwardly applicable to other kinds of scheduled
events such as other sports, award ceremonies, keynote talks, TV shows, etc.
O documento resume as principais informações sobre Doenças Sexualmente Transmissíveis (DSTs). Ele explica que DSTs são infecções que se transmitem através do contato sexual e listas algumas das DSTs mais comuns, incluindo formas de contágio, sintomas e tratamentos. O documento também fornece estatísticas sobre casos de AIDS no Brasil e enfatiza a importância da prevenção através do uso correto de camisinha.
O documento descreve várias Infecções Sexualmente Transmissíveis (ISTs), incluindo seus agentes causadores, sintomas, formas de transmissão e medidas de prevenção. As ISTs discutidas incluem gonorreia, sífilis, candidíase, condiloma, herpes genital, hepatite B e HIV/AIDS. O documento enfatiza a importância de procurar tratamento médico ao notar sintomas e de usar preservativos para prevenir a transmissão dessas doenças.
IST's são infecções sexualmente transmissíveis causadas por bactérias ou vírus que podem ser transmitidos através de relações sexuais desprotegidas. Os sintomas de IST's incluem corrimentos anormais, dores ou úlceras genitais. O único método eficaz de prevenção é o uso consistente de preservativos masculinos durante as relações sexuais.
O documento discute infecções sexualmente transmissíveis (ISTs), incluindo suas principais causas, sintomas e formas de prevenção. As ISTs podem causar doenças pélvicas inflamatórias, infertilidade e complicações durante a gravidez. Grupos de alto risco incluem trabalhadores do sexo, adolescentes, motoristas de caminhão e prisioneiros. O uso correto e consistente de preservativos é a melhor forma de prevenção.
Este documento discute as ISTs (Infecções Sexualmente Transmissíveis). Ele define ISTs como infecções causadas por vírus, bactérias ou protozoários que são transmitidas através de contato sexual íntimo. Ele lista alguns dos principais agentes causadores de ISTs, incluindo vírus como HIV, HPV e herpes, bem como bactérias como clamídia e gonorreia. Finalmente, discute estratégias de prevenção primária, secundária e terciária contra ISTs.
O documento discute infecções sexualmente transmissíveis (ISTs) comuns na adolescência, incluindo sífilis, gonorreia, condiloma, herpes genital, hepatite B, tricomoníase, candidíase, pediculose púbica, clamídia e AIDS. Ele fornece informações sobre a prevenção dessas ISTs.
Towards Real-Time Summarization of Scheduled Events from Twitter StreamsDamiano Spina
This work explores the real-time summarization of sched-
uled events such as soccer games from torrential
ows of Twitter streams. We propose and evaluate an approach
that substantially shrinks the stream of tweets in real-time,
and consists of two steps: (i) sub-event detection, which
determines if something new has occurred, and (ii) tweet se-
lection, which picks a representative tweet to describe each sub-event. We compare the summaries generated in three
languages for all the soccer games in Copa America 2011
to reference live reports oered by Yahoo! Sports journal-
ists. We show that simple text analysis methods which do
not involve external knowledge lead to summaries that cover
84% of the sub-events on average, and 100% of key types of sub-events (such as goals in soccer). Our approach should
be straightforwardly applicable to other kinds of scheduled
events such as other sports, award ceremonies, keynote talks, TV shows, etc.
O documento resume as principais informações sobre Doenças Sexualmente Transmissíveis (DSTs). Ele explica que DSTs são infecções que se transmitem através do contato sexual e listas algumas das DSTs mais comuns, incluindo formas de contágio, sintomas e tratamentos. O documento também fornece estatísticas sobre casos de AIDS no Brasil e enfatiza a importância da prevenção através do uso correto de camisinha.
O documento descreve várias Infecções Sexualmente Transmissíveis (ISTs), incluindo seus agentes causadores, sintomas, formas de transmissão e medidas de prevenção. As ISTs discutidas incluem gonorreia, sífilis, candidíase, condiloma, herpes genital, hepatite B e HIV/AIDS. O documento enfatiza a importância de procurar tratamento médico ao notar sintomas e de usar preservativos para prevenir a transmissão dessas doenças.
IST's são infecções sexualmente transmissíveis causadas por bactérias ou vírus que podem ser transmitidos através de relações sexuais desprotegidas. Os sintomas de IST's incluem corrimentos anormais, dores ou úlceras genitais. O único método eficaz de prevenção é o uso consistente de preservativos masculinos durante as relações sexuais.
O documento discute infecções sexualmente transmissíveis (ISTs), incluindo suas principais causas, sintomas e formas de prevenção. As ISTs podem causar doenças pélvicas inflamatórias, infertilidade e complicações durante a gravidez. Grupos de alto risco incluem trabalhadores do sexo, adolescentes, motoristas de caminhão e prisioneiros. O uso correto e consistente de preservativos é a melhor forma de prevenção.
Este documento discute as ISTs (Infecções Sexualmente Transmissíveis). Ele define ISTs como infecções causadas por vírus, bactérias ou protozoários que são transmitidas através de contato sexual íntimo. Ele lista alguns dos principais agentes causadores de ISTs, incluindo vírus como HIV, HPV e herpes, bem como bactérias como clamídia e gonorreia. Finalmente, discute estratégias de prevenção primária, secundária e terciária contra ISTs.
O documento discute infecções sexualmente transmissíveis (ISTs) comuns na adolescência, incluindo sífilis, gonorreia, condiloma, herpes genital, hepatite B, tricomoníase, candidíase, pediculose púbica, clamídia e AIDS. Ele fornece informações sobre a prevenção dessas ISTs.
Este documento discute as principais infecções sexualmente transmissíveis, incluindo sida, hepatite B e gonorreia. Ele explica o que são ISTs, como são transmitidas através de relações sexuais, e como prevenir e detectar cada uma delas. Finalmente, fornece estatísticas globais sobre a contaminação por essas doenças.
O documento discute doenças sexualmente transmissíveis (DSTs), incluindo suas definições, causas, sintomas e métodos de prevenção. Ele fornece detalhes sobre várias DSTs comuns como sífilis, gonorreia, clamídia e HIV/AIDS, além de abordar estatísticas sobre infecções no Brasil e violência contra mulheres na África do Sul. O documento enfatiza a importância do uso de preservativos para prevenir a transmissão de DSTs.
O documento fornece informações sobre doenças sexualmente transmissíveis (DSTs), seus sintomas, formas de prevenção e tratamento. Ele explica que as DSTs podem ser causadas por vírus, bactérias, fungos e protozoários, são transmitidas principalmente por relações sexuais desprotegidas e, se não tratadas, podem ter complicações graves como esterilidade, câncer e até morte. A mensagem principal é a importância da prevenção, por meio do uso correto e consistente de preservativos, e do tratamento
Each month, join us as we highlight and discuss hot topics ranging from the future of higher education to wearable technology, best productivity hacks and secrets to hiring top talent. Upload your SlideShares, and share your expertise with the world!
Not sure what to share on SlideShare?
SlideShares that inform, inspire and educate attract the most views. Beyond that, ideas for what you can upload are limitless. We’ve selected a few popular examples to get your creative juices flowing.
SlideShare is a global platform for sharing presentations, infographics, videos and documents. It has over 18 million pieces of professional content uploaded by experts like Eric Schmidt and Guy Kawasaki. The document provides tips for setting up an account on SlideShare, uploading content, optimizing it for searchability, and sharing it on social media to build an audience and reputation as a subject matter expert.
A novel incremental clustering for information extraction from social networkseSAT Journals
Abstract
The challenge of this project concentrates upon the issue of synopsis on the remark string regarding the particular message from social media. Because of the more fame of social media, amount of remarks may increment by the side of more ratio directly later the societal message is printed. Clients can want to achieve the detailed comprehension about remark string without study entire remark set, an attempt is made in order to bunch remarks by comparative substance all at once also produce the succinct judgment outline only for this message. Seeing that any time various clients can ask for a synopsis outcome, but the existing clustering strategies cannot fulfill the current requirement of this program. We design an incremental bunching issue for remark string synopsis upon social media also propose Incremental Clustering method it can incrementally bring up to date bunching outcomes including recent arriving remarks. And also, we design a presentation interface comprising of fundamental data, key-terms, and delegate remarks. This brief look presentation interface assists clients to rapidly achieve the outline comprehension about remark string. From the experimental results it is observed that Incremental Clustering method is more efficient than K-Means and Batch clustering methods.
Keywords: Clustering, Summarization, Remark Strings, SNS (Social Network Services).
A novel incremental clustering for information extraction from social networkseSAT Journals
Abstract
The challenge of this project concentrates upon the issue of synopsis on the remark string regarding the particular message from social media. Because of the more fame of social media, amount of remarks may increment by the side of more ratio directly later the societal message is printed. Clients can want to achieve the detailed comprehension about remark string without study entire remark set, an attempt is made in order to bunch remarks by comparative substance all at once also produce the succinct judgment outline only for this message. Seeing that any time various clients can ask for a synopsis outcome, but the existing clustering strategies cannot fulfill the current requirement of this program. We design an incremental bunching issue for remark string synopsis upon social media also propose Incremental Clustering method it can incrementally bring up to date bunching outcomes including recent arriving remarks. And also, we design a presentation interface comprising of fundamental data, key-terms, and delegate remarks. This brief look presentation interface assists clients to rapidly achieve the outline comprehension about remark string. From the experimental results it is observed that Incremental Clustering method is more efficient than K-Means and Batch clustering methods.
Keywords: Clustering, Summarization, Remark Strings, SNS (Social Network Services).
This dissertation analyzes social media data and outlines approaches for understanding online communication and collaboration. It presents algorithms for detecting communities using structural and semantic properties. It analyzes blog subscription patterns and the microblogging phenomenon. Systems are developed for opinion retrieval from blogs and identifying influential users. The growth of social media and tagging behavior are also studied through analysis of tags and social graphs.
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
IRJET- Finding Related Forum Posts through Intention-Based SegmentationIRJET Journal
This document presents a novel technique for finding related discussion posts on forums by segmenting each post into sections based on the intention of the author. Each section aims to convey a different message or objective. Relatedness between posts is determined by comparing sections that share the same intention, rather than comparing the full text of posts. The technique involves identifying sections within each post using linguistic and semantic cues. Sections with the same intention are then clustered together. The effectiveness of this intention-based segmentation for suggesting related forum posts is evaluated on real user data from different domains. The proposed approach is found to be more effective at determining post relatedness than direct text comparisons of full posts.
Multi-Mode Conceptual Clustering Algorithm Based Social Group Identification ...inventionjournals
The problem of web search time complexity and accuracy has been visited in many research papers, and the authors discussed many approaches to improve the search performance. Still the approaches does not produce any noticeable improvement and struggles with more time complexity as well. To overcome the issues identified, an efficient multi mode conceptual clustering algorithm has been discussed in this paper, which identifies the similar interested user groups by clustering their search context according to different conceptual queries. Identified user groups are shared with the related conceptual queries and their results to reduce the time complexity. The multi mode conceptual clustering, performs grouping of search queries and users according to number of users and their search pattern. The concept of search is identified by using Natural language processing methods and the web logs produced by the default web search engines. The author designed a dedicated web interface to collect the web log about the user search and the same data has been used to cluster the social groups according to number of conceptual queries. The search results has been shared between the users of identified social groups which reduces the search time complexity and improves the efficiency of web search in better manner
A Hybrid Approach for Supervised Twitter Sentiment Classification ....................................................1
K. Revathy and Dr. B. Sathiyabhama
A Survey of Dynamic Duty Cycle Scheduling Scheme at Media Access Control Layer for Energy
Conservation .....................................................................................................................................1
Prof. M. V. Nimbalkar and Sampada Khandare
A Survey on Privacy Preserving Data Mining Techniques ....................................................................1
A. K. Ilavarasi, B. Sathiyabhama and S. Poorani
An Ontology Based System for Predicting Disease using SWRL Rules ...................................................1
Mythili Thirugnanam, Tamizharasi Thirugnanam and R. Mangayarkarasi
Performance Evaluation of Web Services in C#, JAVA, and PHP ..........................................................1
Dr. S. Sagayaraj and M. Santhosh Kumar
Semi-Automated Polyhouse Cultivation Using LabVIEW......................................................................1
Prathiba Jonnala and Sivaji Satrasupalli
Performance of Biometric Palm Print Personal Identification Security System Using Ordinal Measures 1
V. K. Narendira Kumar and Dr. B. Srinivasan
MIMO System for Next Generation Wireless Communication..............................................................1
Sharif, Mohammad Emdadul Haq and Md. Arif Rana
APPLYING OPINION MINING TO ORGANIZE WEB OPINIONSIJCSEA Journal
Rapid increase of opinions on the web requires an effectual system to organize opinions. Opinion mining is a realistically plot and demanding field devoted to detect subjective content in text documents. If opinions are non-structured then it’s difficult for customers and organizations to understand. This study proposes an approach focusing on designing a system to organize web opinions at the time when user is posting, before actually being extracted by expertise. New system (Opinion Organization System) provides four stages. In first stage, it provides a list of several product categories and user selects at least one. In second stage, a list of selected product relevant features is displayed to the user. In third stage, user firstly selects features for which wants to express opinions, then uses polarity based P set and N set containing adjective words list and in fourth stage, uses thumb selection table to add opinions.
Framework for Product Recommandation for Review Datasetrahulmonikasharma
In the social networking era, product reviews have a significant influence on the purchase decisions of customers so the market has recognized this problem The problem with this is that the customers do not know how these systems work which results in trust issues. Therefore a different system is needed that helps customers with their need to process the information in product reviews. There are different approaches and algorithms of data filtering and recommendation .Most existing recommender systems were developed for commercial domains with millions of users. In this paper we have discussed the recommendation system and its related research and implemented different techniques of the recommender system .
IRJET- Sentimental Prediction of Users Perspective through Live Streaming : T...IRJET Journal
This document proposes a system to analyze sentiment from live streaming text and videos on websites like Twitter and YouTube. It uses an algorithm that calculates sentiment scores for words and sentences and classifies them as positive or negative. The system accesses streaming data through API keys and performs sentiment analysis on both text and videos to improve accuracy. It stores the results in a MongoDB database for future reference. The goal is to help users analyze sentiment toward any search keyword from streaming data in real-time.
Este documento discute as principais infecções sexualmente transmissíveis, incluindo sida, hepatite B e gonorreia. Ele explica o que são ISTs, como são transmitidas através de relações sexuais, e como prevenir e detectar cada uma delas. Finalmente, fornece estatísticas globais sobre a contaminação por essas doenças.
O documento discute doenças sexualmente transmissíveis (DSTs), incluindo suas definições, causas, sintomas e métodos de prevenção. Ele fornece detalhes sobre várias DSTs comuns como sífilis, gonorreia, clamídia e HIV/AIDS, além de abordar estatísticas sobre infecções no Brasil e violência contra mulheres na África do Sul. O documento enfatiza a importância do uso de preservativos para prevenir a transmissão de DSTs.
O documento fornece informações sobre doenças sexualmente transmissíveis (DSTs), seus sintomas, formas de prevenção e tratamento. Ele explica que as DSTs podem ser causadas por vírus, bactérias, fungos e protozoários, são transmitidas principalmente por relações sexuais desprotegidas e, se não tratadas, podem ter complicações graves como esterilidade, câncer e até morte. A mensagem principal é a importância da prevenção, por meio do uso correto e consistente de preservativos, e do tratamento
Each month, join us as we highlight and discuss hot topics ranging from the future of higher education to wearable technology, best productivity hacks and secrets to hiring top talent. Upload your SlideShares, and share your expertise with the world!
Not sure what to share on SlideShare?
SlideShares that inform, inspire and educate attract the most views. Beyond that, ideas for what you can upload are limitless. We’ve selected a few popular examples to get your creative juices flowing.
SlideShare is a global platform for sharing presentations, infographics, videos and documents. It has over 18 million pieces of professional content uploaded by experts like Eric Schmidt and Guy Kawasaki. The document provides tips for setting up an account on SlideShare, uploading content, optimizing it for searchability, and sharing it on social media to build an audience and reputation as a subject matter expert.
A novel incremental clustering for information extraction from social networkseSAT Journals
Abstract
The challenge of this project concentrates upon the issue of synopsis on the remark string regarding the particular message from social media. Because of the more fame of social media, amount of remarks may increment by the side of more ratio directly later the societal message is printed. Clients can want to achieve the detailed comprehension about remark string without study entire remark set, an attempt is made in order to bunch remarks by comparative substance all at once also produce the succinct judgment outline only for this message. Seeing that any time various clients can ask for a synopsis outcome, but the existing clustering strategies cannot fulfill the current requirement of this program. We design an incremental bunching issue for remark string synopsis upon social media also propose Incremental Clustering method it can incrementally bring up to date bunching outcomes including recent arriving remarks. And also, we design a presentation interface comprising of fundamental data, key-terms, and delegate remarks. This brief look presentation interface assists clients to rapidly achieve the outline comprehension about remark string. From the experimental results it is observed that Incremental Clustering method is more efficient than K-Means and Batch clustering methods.
Keywords: Clustering, Summarization, Remark Strings, SNS (Social Network Services).
A novel incremental clustering for information extraction from social networkseSAT Journals
Abstract
The challenge of this project concentrates upon the issue of synopsis on the remark string regarding the particular message from social media. Because of the more fame of social media, amount of remarks may increment by the side of more ratio directly later the societal message is printed. Clients can want to achieve the detailed comprehension about remark string without study entire remark set, an attempt is made in order to bunch remarks by comparative substance all at once also produce the succinct judgment outline only for this message. Seeing that any time various clients can ask for a synopsis outcome, but the existing clustering strategies cannot fulfill the current requirement of this program. We design an incremental bunching issue for remark string synopsis upon social media also propose Incremental Clustering method it can incrementally bring up to date bunching outcomes including recent arriving remarks. And also, we design a presentation interface comprising of fundamental data, key-terms, and delegate remarks. This brief look presentation interface assists clients to rapidly achieve the outline comprehension about remark string. From the experimental results it is observed that Incremental Clustering method is more efficient than K-Means and Batch clustering methods.
Keywords: Clustering, Summarization, Remark Strings, SNS (Social Network Services).
This dissertation analyzes social media data and outlines approaches for understanding online communication and collaboration. It presents algorithms for detecting communities using structural and semantic properties. It analyzes blog subscription patterns and the microblogging phenomenon. Systems are developed for opinion retrieval from blogs and identifying influential users. The growth of social media and tagging behavior are also studied through analysis of tags and social graphs.
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
IRJET- Finding Related Forum Posts through Intention-Based SegmentationIRJET Journal
This document presents a novel technique for finding related discussion posts on forums by segmenting each post into sections based on the intention of the author. Each section aims to convey a different message or objective. Relatedness between posts is determined by comparing sections that share the same intention, rather than comparing the full text of posts. The technique involves identifying sections within each post using linguistic and semantic cues. Sections with the same intention are then clustered together. The effectiveness of this intention-based segmentation for suggesting related forum posts is evaluated on real user data from different domains. The proposed approach is found to be more effective at determining post relatedness than direct text comparisons of full posts.
Multi-Mode Conceptual Clustering Algorithm Based Social Group Identification ...inventionjournals
The problem of web search time complexity and accuracy has been visited in many research papers, and the authors discussed many approaches to improve the search performance. Still the approaches does not produce any noticeable improvement and struggles with more time complexity as well. To overcome the issues identified, an efficient multi mode conceptual clustering algorithm has been discussed in this paper, which identifies the similar interested user groups by clustering their search context according to different conceptual queries. Identified user groups are shared with the related conceptual queries and their results to reduce the time complexity. The multi mode conceptual clustering, performs grouping of search queries and users according to number of users and their search pattern. The concept of search is identified by using Natural language processing methods and the web logs produced by the default web search engines. The author designed a dedicated web interface to collect the web log about the user search and the same data has been used to cluster the social groups according to number of conceptual queries. The search results has been shared between the users of identified social groups which reduces the search time complexity and improves the efficiency of web search in better manner
A Hybrid Approach for Supervised Twitter Sentiment Classification ....................................................1
K. Revathy and Dr. B. Sathiyabhama
A Survey of Dynamic Duty Cycle Scheduling Scheme at Media Access Control Layer for Energy
Conservation .....................................................................................................................................1
Prof. M. V. Nimbalkar and Sampada Khandare
A Survey on Privacy Preserving Data Mining Techniques ....................................................................1
A. K. Ilavarasi, B. Sathiyabhama and S. Poorani
An Ontology Based System for Predicting Disease using SWRL Rules ...................................................1
Mythili Thirugnanam, Tamizharasi Thirugnanam and R. Mangayarkarasi
Performance Evaluation of Web Services in C#, JAVA, and PHP ..........................................................1
Dr. S. Sagayaraj and M. Santhosh Kumar
Semi-Automated Polyhouse Cultivation Using LabVIEW......................................................................1
Prathiba Jonnala and Sivaji Satrasupalli
Performance of Biometric Palm Print Personal Identification Security System Using Ordinal Measures 1
V. K. Narendira Kumar and Dr. B. Srinivasan
MIMO System for Next Generation Wireless Communication..............................................................1
Sharif, Mohammad Emdadul Haq and Md. Arif Rana
APPLYING OPINION MINING TO ORGANIZE WEB OPINIONSIJCSEA Journal
Rapid increase of opinions on the web requires an effectual system to organize opinions. Opinion mining is a realistically plot and demanding field devoted to detect subjective content in text documents. If opinions are non-structured then it’s difficult for customers and organizations to understand. This study proposes an approach focusing on designing a system to organize web opinions at the time when user is posting, before actually being extracted by expertise. New system (Opinion Organization System) provides four stages. In first stage, it provides a list of several product categories and user selects at least one. In second stage, a list of selected product relevant features is displayed to the user. In third stage, user firstly selects features for which wants to express opinions, then uses polarity based P set and N set containing adjective words list and in fourth stage, uses thumb selection table to add opinions.
Framework for Product Recommandation for Review Datasetrahulmonikasharma
In the social networking era, product reviews have a significant influence on the purchase decisions of customers so the market has recognized this problem The problem with this is that the customers do not know how these systems work which results in trust issues. Therefore a different system is needed that helps customers with their need to process the information in product reviews. There are different approaches and algorithms of data filtering and recommendation .Most existing recommender systems were developed for commercial domains with millions of users. In this paper we have discussed the recommendation system and its related research and implemented different techniques of the recommender system .
IRJET- Sentimental Prediction of Users Perspective through Live Streaming : T...IRJET Journal
This document proposes a system to analyze sentiment from live streaming text and videos on websites like Twitter and YouTube. It uses an algorithm that calculates sentiment scores for words and sentences and classifies them as positive or negative. The system accesses streaming data through API keys and performs sentiment analysis on both text and videos to improve accuracy. It stores the results in a MongoDB database for future reference. The goal is to help users analyze sentiment toward any search keyword from streaming data in real-time.
MingleSpot is a social networking website that allows users to connect with friends, search for people with shared interests, and join online communities. Key features include user profiles, searching for friends and adding them, asking and answering questions, creating and participating in polls, joining or creating interest groups, sharing opinions, finding local information, and sending messages to connections. The goal is to make it easy for users to stay connected with friends and family, meet new people, and grow their business networks. Technologies used include Java, servlets, JSP, and JavaScript.
MingleSpot is a social networking website that allows users to connect with friends, search for people with shared interests, and join online communities. Key features include user profiles, searching for friends, asking and answering questions, creating and participating in polls, joining or creating interest groups, sharing opinions, accessing local information, and sending messages to connections. The website aims to help users stay connected with existing contacts and make new connections. Technologies used include Java programming languages and related tools.
There’s a dirty secret in the turf war between agile, lean, and waterfall: they each use the same product development process. What’s different isn’t their process, but how they apply design activities in different ways to eke out different design value.
So how can you alter the design process? Even better, how can you customize the process to provide more value for the way your organization works? How should you change the design process from sprint to sprint to get the most value out of your design activities?
How do you hack user experience?
This document discusses a product analyst advisor software that uses natural language processing techniques like sentiment analysis to analyze customer reviews and sentiments about products. It extracts reviews from various websites about a product being researched and processes the data to provide useful insights. The insights help users easily select the best available option. The system architecture involves scraping live data from websites, using deep learning algorithms to analyze reviews for sentiments, and displaying product insights. It uses BERT for sentiment analysis and frameworks like Django and ReactJS. Web scraping is used to extract review data for analysis and providing recommendations to users.
Running head DEPRESSION PREDICTION DRAFT1DEPRESSION PREDICTI.docxhealdkathaleen
This paper explores using machine learning and natural language processing techniques to analyze social media posts and other online behaviors to detect levels of depression in individuals. Key approaches discussed include using k-means clustering and neural networks on sources like reviews, posts, and articles. Link mining and weighted network modeling are also used to understand relationships between online content and detect patterns associated with depression. The goal is to help identify individuals who may be depressed so counselors can better assist them.
This document analyzes data from online forums used by two software companies, Salesforce and SAP, to crowdsource ideas for new software features from customers. The analysis finds that a small core group of users in each forum are responsible for generating a large proportion of implemented ideas. Betweenness centrality is identified as an effective measure for identifying influential users. Commenting on ideas is found to be more effective than voting at fostering community formation among participants.
A Visual Guide to 1 Samuel | A Tale of Two HeartsSteve Thomason
These slides walk through the story of 1 Samuel. Samuel is the last judge of Israel. The people reject God and want a king. Saul is anointed as the first king, but he is not a good king. David, the shepherd boy is anointed and Saul is envious of him. David shows honor while Saul continues to self destruct.
This document provides an overview of wound healing, its functions, stages, mechanisms, factors affecting it, and complications.
A wound is a break in the integrity of the skin or tissues, which may be associated with disruption of the structure and function.
Healing is the body’s response to injury in an attempt to restore normal structure and functions.
Healing can occur in two ways: Regeneration and Repair
There are 4 phases of wound healing: hemostasis, inflammation, proliferation, and remodeling. This document also describes the mechanism of wound healing. Factors that affect healing include infection, uncontrolled diabetes, poor nutrition, age, anemia, the presence of foreign bodies, etc.
Complications of wound healing like infection, hyperpigmentation of scar, contractures, and keloid formation.
How to Make a Field Mandatory in Odoo 17Celine George
In Odoo, making a field required can be done through both Python code and XML views. When you set the required attribute to True in Python code, it makes the field required across all views where it's used. Conversely, when you set the required attribute in XML views, it makes the field required only in the context of that particular view.
Temple of Asclepius in Thrace. Excavation resultsKrassimira Luka
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Ists
1. ISTS
Abstract:
Social network services (SNS) are prevalent and have become important
communication platforms in our daily life. Our algorithms process collections of
short posts on specific topics on the well-known site called Twitter and create short
summaries from these collections of posts on a specific topic. The goal is to
produce summaries that are similar to what a human would delivered and also
produce for the summaries result from the collection of user’s post. So construct
the model for a novel incremental clustering problem for comment stream
summarization on SNS. Moreover, we propose IncreSTS algorithm that can
incrementally update clustering results with latest incoming comments in real time.
Furthermore, we design an at-a-glance visualization interface to help users easily
and rapidly get an overview summary. From extensive experimental results and a
real case demonstration, we verify that IncreSTS possesses the advantages of high
efficiency, high scalability, and better handling outliers.
2. Introduction:
A social network is a social structure made up of a set of social actors (such
as individuals or organizations) and a set of the dyadic ties between these actors.
The social network perspective provides a set of methods for analyzing the
structure of whole social entities as well as a variety of theories explaining the
patterns observed from the structures.
Due to the popularity and convenience of these platforms, celebrities,
corporations, and organizations also set up social pages to interact with their fans
and the public. Note that for each message, users are able to express their opinions
by forwarding, giving a like, and leaving comments on it. Not only the quantity of
comments is large, but also the generation rate is remarkably high.
Users unnecessarily and almost impossibly go over the whole comment list
of each message. However, we may still desire to know what are they talking about
and what are the opinions of these discussion participants. Moreover, celebrities
and corporations will have high interest to understand how their fans and
customers reacting to certain topics and content. With these motivations,
Inspired to develop an advanced summarization technique targeting at
comment streams in social network services. Numerous studies and systems have
proposed techniques and mechanisms to generate various types of summaries on
3. comment streams. One major category aims to extract representative and
significant comments from messy discussion.
Our proposed system does not focus on traditional comment streams that
usually express more complete information, such as the discussion on products or
movies. We target at comment streams in SNS that are in short text style with
casual language usage.
For each social message, our main objective is to cluster comments with
similar content together and generate a concise opinion summary for this message.
We want to discover how many different group opinions exist and provide an
overview of each group to make users easily and rapidly understand.
For instance, when Lady Gaga uploads a photo to SNS, there are hundreds
and thousands of comments given by her fans during a short period of time.
Some of them may say that she is very beautiful, and another group of fans
may think that the outfit is too weird. Even more, some may particularly discuss
the hair style of this photo.
Our goal is developing an efficient and effective technique to identify the
clusters of these comments. Note that this problem is clearly different from
existing research and possesses numerous unique characteristics and challenges.
Explore the problem of incremental short text summarization on comment
streams from social network services. We model this problem as an incremental
4. clustering task and propose the Incremental Short Text Summarization algorithm
to discover the top-k clusters including different groups of opinions towards one
social message.
For each comment cluster, important and common terms will be extracted to
construct a key-term cloud. This key-term cloud provides an at-a-glance
presentation that users can easily and rapidly understand the main points of similar
comments in a cluster. Moreover, representative comments in each group will also
be identified.
5. Existing System:
In social network consist of problems during when a user uploads a photo to
social network services; there are hundreds and thousands of comments given by
her fans during a short period of time. Some of them may say that she is very
beautiful, and another group of fans may think that the outfit is too weird.
Even more, some may particularly discuss the hair style of this photo.
Therefore, our goal is developing an efficient and effective technique to identify
the clusters of these comments.
The quantity of comments may increase at a high rate right after a social
message is published. Moreover, distinct users will request the summary result at
any moment. For these reasons, in order to immediately generate a summary based
on the current comment stream, an incremental approach is preferable to meet the
real-time needs of this application.
The comments in social network service are usually short, and users widely
make use of informal and unstructured texts that contain acronyms, shortening
words, etc.
This phenomenon increases the difficulty of determining the similarity
between comments. On the other hand, it is worth mentioning that instead of
emphasizing on the quality of clustering, the most crucial point of this task is to
6. produce a general summary promptly so that users can easily get the overview of a
comment stream. It can be perceived that this problem is able to be modeled as a
clustering task. However, traditional clustering methods have several inherent
restrictions that cannot be directly applied here.
The computational complexity of existing methods is high, and they cannot
straightforwardly adapt to satisfy the incremental need. Moreover, in this problem,
defining the number of desired clusters in advance is unreasonable, which is
required in many clustering algorithms. In addition, there will be a lot of outliers in
a comment stream, meaning that without employing a good strategy for selecting
initial cluster centers, existing method may be prone to poorresults.
Disadvantages:
o The difficulty of determining the similarity between comments
is more.
o Cluster identification is difficult one.
o Computational complexity is High.
o Due to sparse information contained in each comment, these
approaches are not suitable for short text summarization
especially when the number of comments is not large.
7. Problem Definition:
To discover top-k groups where the comments in the same group express
similar opinions while the comments belonging to different groups express diverse
points of view. Once a message is posted on SNS, users can leave comments
immediately and the number of comments may rise quickly and continuously.
Readers are usually unwilling to go over the whole list of comments, but
they may request to see the summary at any moment. adopt the term vector model,
and therefore each comment is transformed into a set of n-gram terms by the NLP
module. Since informal and unstructured texts are widely used on SNS, we also
apply some heuristics to enhance the quality of n-gram terms that can better
represent each comment.
In such a context, whenever a request is received, the proposed IncreSTS
algorithm will efficiently produce top-k groups of opinions in real time. It can be
perceived that it is infeasible to repeatedly carry out the complete clustering task
due to the high complexity. For this reason, we design the IncreSTS algorithm in
incremental manner, meaning that the clustering result of the previous phase will
be leveraged to generate the current summary with newly-incoming comments.
For the visualization interface, representative terms will be extracted to form
a key-term cloud for each group. Thus, users will be provided a concise,
informative, and at-a-glace presentation that can help them easily comprehend the
main points of responses to one message on social network services.
8. ProposedSystem:
Explore the problem of incremental short text summarization on comment
streams from social network services. To model this problem as an incremental
clustering task and propose Incremental Short Text Summarization algorithm to
discover the top-k clusters including different groups of opinions towards one
social message. For each comment cluster, important and common terms will be
extracted to construct a key-term cloud. This key-term cloud provides an at-a-
glance presentation that users can easily and rapidly understand the main points of
similar comments in a cluster.
Representative comments in each group will also be identified. Our
objective is to generate an informative, concise, and impressive interface that can
help users get an overview understanding without reading all comments.our
proposed system depends on a fully incremental algorithm that is almost
parameterfree and can handle the outlier problem.
The most significant advantage of our algorithm is its high efficiency,
indicating that it can generate clustering results with latest incoming comments in
real time. These capabilities certainly meet the need of comment stream
summarization on social network serices.
To verify the effectiveness of IncreSTS algorithm, we collect real comment
streams from Facebook and conduct extensive experiments with comparative
methods to show the strength and superiority of our approach. a novel incremental
9. clustering problem based on the requirements of comment stream summarization
on SNS.
To propose IncreSTS algorithm that can incrementally update clustering
results with latest incoming comments in real time. We design an at-a-glance
presentation, which is concise, informative, and impressive, to help users easily
and rapidly get an overview understanding of a comment stream.
Social network services are not restricted to well-known social websites,
such as Facebook, Twitter, etc. The Web services providing interaction
functionality for users can be generally included. for each word, the process of
punctuation removal will be applied to eliminate unnecessary punctuation marks
connected with this word. Moreover, we develop the heuristic process of redundant
character removal, designed for restoring words on SNS. It can be observed that
casual language style is commonly used on SNS.
Users often emphasize the emotion by repeating characters in a word. This
phenomenon certainly causes the problem of not being able to correctly identify
the original words. To copewith this problem,
Finally examine each word to find out whether there is any character
consecutively appearing more than three times. If this situation is detected,
appended characters will be regarded as redundant, and only one character will be
retained.
Advantages:
High efficiency.
High scalability, and better handling outliers,
10. Justifies the practicability of Incremental Short Text Summarization
on the target problem.
Algorithm:
Input: C: the set of previous clustering result
vnew: the newly-incoming comment
θr: the radius threshold
Output: top-k clusters which have top-k most comments
1. Ca = {Ci | Ci is an element of C ∩ dis(vnew,Ci) is not infinite};
2. Cb= {Cj | Cj is an element of Ca ∩ dis(vnew,Cj) < θr};
3. if Cb is not empty
4. Add vnew into Cadded which have most comments in Cb;
5. Initialize Cchanged= Ø ;
6. for each element Ci of Ca where Ci ≠ Cadded
7. for each comment vj in Ci
8. if dis(vj,Cadded) < θr
9. Add vj into Cadded;
10. Exclude vj from Ci;
11. Cchanged = Cchanged∪ Ci;
12. for each element Ci of Cchanged
13. while V = {vj | dis(vj,Ci) ≧ θr} is not empty
14. Exclude all elements in V from Ci;
15. Try to add each comment in V into other clusters
from large to small sizes;
16. else
17. Form a new cluster Cnew with the comment vnew;
18. C = C ∪ Cnew;
11. 19. Output top-k clusters in C which have top-k most comments;
End
Conclusion:
To enable the capability of comment stream summarization on SNS, we
model a novel incremental clustering problem and propose the algorithm
Incremental Short Text Summarization, which can incrementally update clustering
results with latest incoming comments in real time. With the output of IncreSTS,
we design a visualization interface consisting of basic information, key-term
clouds, and representative comments. This at a glance of users to easily and rapidly
get an overview understanding of a comment stream. From extensive experimental
results and a real case demonstration, we verify that IncreSTS possesses the
advantages of high efficiency, high scalability, and better handling outliers, which
justifies the practicability of IncreSTS on the target problem.
12. Future Enhancement:
In the high popularity of social security serices, the number of comments for
a specific message may increase very quickly, and users will request to view the
summary of comments at any time. Moreover, since new messages appear
continuously, users generally only view the summary of a specific message once
and will not go back to browse the updated summary in the future. In such a
context, to immediately produce the latest top-k clusters, we propose the IncreSTS
algorithm that has the capability of incremental update.