Human Interaction in meetings is one of the famous fields of social dynamics. Meeting is integral part of
every organization. In this, meeting outcome is extracted using tree based approach. Meetings contents or
conversation are available in forms such as audio, video and text. In this, pattern of meeting is extracted
from text document. An interaction is represented in the form of tree. Meeting Output is generated using
data mining technique. Firstly the contents are filtered, extracted and steamed. Secondly classification is
done into six categories propose, comment, acknowledgement, request Info, ask Opinion, pos Opinion, and
neg Opinion. Next the interaction tree is constructed which represent the interaction flow of meeting.
Finally the meeting output is generated from interaction tree using frequent pattern mining algorithm. The
behavior of person is determined which includes a person who proposed a lot of ideas, a person with
positive or negative attitude.
Human Interaction in meetings is one of the famous fields of social dynamics. Meeting is integral part of
every organization. In this, meeting outcome is extracted using tree based approach. Meetings contents or
conversation are available in forms such as audio, video and text. In this, pattern of meeting is extracted
from text document. An interaction is represented in the form of tree. Meeting Output is generated using
data mining technique. Firstly the contents are filtered, extracted and steamed. Secondly classification is
done into six categories propose, comment, acknowledgement, request Info, ask Opinion, pos Opinion, and
neg Opinion. Next the interaction tree is constructed which represent the interaction flow of meeting.
Finally the meeting output is generated from interaction tree using frequent pattern mining algorithm. The
behavior of person is determined which includes a person who proposed a lot of ideas, a person with
positive or negative attitude.
Sentiment classification aims to detect information such as opinions, explicit , implicit feelings expressed
in text. The most existing approaches are able to detect either explicit expressions or implicit expressions of
sentiments in the text separately. In this proposed framework it will detect both Implicit and Explicit
expressions available in the meeting transcripts. It will classify the Positive, Negative, Neutral words and
also identify the topic of the particular meeting transcripts by using fuzzy logic. This paper aims to add
some additional features for improving the classification method. The quality of the sentiment classification
is improved using proposed fuzzy logic framework .In this fuzzy logic it includes the features like Fuzzy
rules and Fuzzy C-means algorithm.The quality of the output is evaluated using the parameters such as
precision, recall, f-measure. Here Fuzzy C-means Clustering technique measured in terms of Purity and
Entropy. The data set was validated using 10-fold cross validation method and observed 95% confidence
interval between the accuracy values .Finally, the proposed fuzzy logic method produced more than 85 %
accurate results and error rate is very less compared to existing sentiment classification techniques.
Multi-mediated community structure in a socio-technical networksuthers
Suthers, D. D., & Chu, K.-H. (2012, April 29-May 2, 2012). Multi-mediated community structure in a socio-technical network. Paper presented at the Learning Analytics and Knowledge 2012 conference
Human Interaction in meetings is one of the famous fields of social dynamics. Meeting is integral part of
every organization. In this, meeting outcome is extracted using tree based approach. Meetings contents or
conversation are available in forms such as audio, video and text. In this, pattern of meeting is extracted
from text document. An interaction is represented in the form of tree. Meeting Output is generated using
data mining technique. Firstly the contents are filtered, extracted and steamed. Secondly classification is
done into six categories propose, comment, acknowledgement, request Info, ask Opinion, pos Opinion, and
neg Opinion. Next the interaction tree is constructed which represent the interaction flow of meeting.
Finally the meeting output is generated from interaction tree using frequent pattern mining algorithm. The
behavior of person is determined which includes a person who proposed a lot of ideas, a person with
positive or negative attitude.
Sentiment classification aims to detect information such as opinions, explicit , implicit feelings expressed
in text. The most existing approaches are able to detect either explicit expressions or implicit expressions of
sentiments in the text separately. In this proposed framework it will detect both Implicit and Explicit
expressions available in the meeting transcripts. It will classify the Positive, Negative, Neutral words and
also identify the topic of the particular meeting transcripts by using fuzzy logic. This paper aims to add
some additional features for improving the classification method. The quality of the sentiment classification
is improved using proposed fuzzy logic framework .In this fuzzy logic it includes the features like Fuzzy
rules and Fuzzy C-means algorithm.The quality of the output is evaluated using the parameters such as
precision, recall, f-measure. Here Fuzzy C-means Clustering technique measured in terms of Purity and
Entropy. The data set was validated using 10-fold cross validation method and observed 95% confidence
interval between the accuracy values .Finally, the proposed fuzzy logic method produced more than 85 %
accurate results and error rate is very less compared to existing sentiment classification techniques.
Multi-mediated community structure in a socio-technical networksuthers
Suthers, D. D., & Chu, K.-H. (2012, April 29-May 2, 2012). Multi-mediated community structure in a socio-technical network. Paper presented at the Learning Analytics and Knowledge 2012 conference
Online interview is not a new thing but in this covid-19 situation it seems to be the only option. However, assessing the candidate on a video call may not be that effective. Having an AI based Interview Assessment System could prove to be useful, which would take input as speech and will give output as detailed analysis of that speech. While most the research work currently done focuses only on finding sentiment or personality from speech, our system aims to extract multiple information from the speech and provide a detailed analysis. The analysis would include a detailed report containing results about confidence level of the person, his/her emotional state, speed of the speech, frequently repeated words and also personality reflected by that speech. An interview panel consists of various members focusing on different aspect of the answer given by the candidate, some focus on technical correctness while, some simply want to check the communication skills of the candidate. Having an AI system giving a report on the soft skills part would reduce the work for interviewer and he/she could give complete focus on the technical correctness of the answer. This could eventually help save time and resources used by organizations for hiring process. This intention of creating this system is to assist the interview process and give analysis report based on the speech input instead a giving a verdict about selection of the candidate. Thus, this system could use not only by the interviewers but also by the candidates. The output provided would be a detailed report which could prove to be a good feedback for the students who are preparing for the interview. Having a feedback would help candidates work on their week points and thus perform better in further interviews.
Generating domain specific sentiment lexicons using the Web Directory acijjournal
In this paper we aim at proposing a method to automatically build a sentiment lexicon which is domain based. There has been a demand for the construction of generated and labeled sentiment lexicon. For data on the social web (E.g., tweets), methods which make use of the synonymy relation don't work well, as we completely ignore the significance of terms belonging to specific domains. Here we propose to
generate a sentiment lexicon for any domain specified, using a twofold method. First we build sentiment scores using the micro-blogging data, and then we use these scores on the ontological structure provided by Open Directory Project [1], to build a custom sentiment lexicon for analyzing domain specific microblogging data.
Speaker specific feature based clustering and its applications in language in...IJECEIAES
Forensic speaker recognition (FSR) is the process of determining whether the source of a questioned voice recording (trace) is of a specific individual (suspected speaker). Most existing methods measure inter-utterance similarities directly based on spectrum-based characteristics, the resulting clusters may not be well related to speaker’s, but rather to different acoustic classes. This research addresses this deficiency by projecting languageindependent utterances into a reference space equipped to cover the standard voice features underlying the entire utterance set. Then a clustering approach is proposed based on the peak approximation in order to maximize the similarities between language-independent utterances within all clusters. This method uses a K-medoid, Fuzzy C-means, Gustafson and Kessel and Gath-Geva algorithm to evaluate the cluster to which each utterance should be allocated, overcoming the disadvantage of traditional hierarchical clustering that the ultimate outcome can only hit the optimum recognition efficiency. The recognition efficiency of K-medoid, Fuzzy C-means, Gustafson and Kessel and Gath-Geva clustering algorithms are 95.2%, 97.3%, 98.5% and 99.7% and EER are 3.62%, 2.91 %, 2.82%, and 2.61% respectively. The EER improvement of the Gath-Geva technique based FSRsystem compared with Gustafson and Kessel and Fuzzy C-means is 8.04% and 11.49% respectively.
A Text Mining Research Based on LDA Topic Modellingcsandit
A Large number of digital text information is gener
ated every day. Effectively searching,
managing and exploring the text data has become a m
ain task. In this paper, we first represent
an introduction to text mining and a probabilistic
topic model Latent Dirichlet allocation. Then
two experiments are proposed - Wikipedia articles a
nd users’ tweets topic modelling. The
former one builds up a document topic model, aiming
to a topic perspective solution on
searching, exploring and recommending articles. The
latter one sets up a user topic model,
providing a full research and analysis over Twitter
users’ interest. The experiment process
including data collecting, data pre-processing and
model training is fully documented and
commented. Further more, the conclusion and applica
tion of this paper could be a useful
computation tool for social and business research.
The peer-reviewed International Journal of Engineering Inventions (IJEI) is started with a mission to encourage contribution to research in Science and Technology. Encourage and motivate researchers in challenging areas of Sciences and Technology.
A FILM SYNOPSIS GENRE CLASSIFIER BASED ON MAJORITY VOTEkevig
We propose an automatic classification system of movie genres based on different features from their textual
synopsis. Our system is first trained on thousands of movie synopsis from online open databases, by learning relationships between textual signatures and movie genres. Then it is tested on other movie synopsis,
and its results are compared to the true genres obtained from the Wikipedia and the Open Movie Database
(OMDB) databases. The results show that our algorithm achieves a classification accuracy exceeding 75%.
The community detection in complex networks has attracted a growing interest and is the subject of several
researches that have been proposed to understand the network structure and analyze the network
properties. In this paper, we give a thorough overview of different community discovery strategies, we
propose taxonomy of these methods, and we specify the differences between the suggested classes which
helping designers to compare and choose the most suitable strategy for the various types of network
encountered in the real world.
A FILM SYNOPSIS GENRE CLASSIFIER BASED ON MAJORITY VOTEijnlc
We propose an automatic classification system of movie genres based on different features from their textual synopsis. Our system is first trained on thousands of movie synopsis from online open databases, by learning relationships between textual signatures and movie genres. Then it is tested on other movie synopsis, and its results are compared to the true genres obtained from the Wikipedia and the Open Movie Database
(OMDB) databases. The results show that our algorithm achieves a classification accuracy exceeding 75%.
Extracting frequent pattern from Human Interaction in Meeting using Tree base...ijcax
Human Interaction in meetings is one of the famous fields of social dynamics. Meeting is integral part of
every organization. In this, meeting outcome is extracted using tree based approach. Meetings contents or
conversation are available in forms such as audio, video and text. In this, pattern of meeting is extracted
from text document. An interaction is represented in the form of tree. Meeting Output is generated using
data mining technique. Firstly the contents are filtered, extracted and steamed. Secondly classification is
done into six categories propose, comment, acknowledgement, request Info, ask Opinion, pos Opinion, and
neg Opinion. Next the interaction tree is constructed which represent the interaction flow of meeting.
Finally the meeting output is generated from interaction tree using frequent pattern mining algorithm. The
behavior of person is determined which includes a person who proposed a lot of ideas, a person with
positive or negative attitude.
Tree Based Mining for Discovering Patterns of Human Interactions in MeetingsIJERA Editor
Meetings are an integral part of workplace dynamics also an important communication and coordination activity of teams: statuses are discussed, decisions, alternatives are considered, details are explained and ideas are generated. In this work, data mining techniques to detect and analyze frequent interaction patterns. We look forward to discover various types of new knowledge on interactions. An interaction tree pattern mining algorithms was proposed to analyze tree structures and extract interaction flow patterns. In this paper we propose the tree based mining for human interaction flow in a discussion session is represented as a tree. In this work we extend an interaction tree mining algorithm in three ways. First, we propose a mining method to extract frequent patterns of human interaction. Second, we explore embedded sub tree mining for hidden interaction pattern discovery. Third, we propose temporal data mining techniques for extracting the temporal patterns from the captured content of time series of different meetings in particular time periods such as month or year. Because of the human integration activities varied based on time and experience of events. For extracting temporal pattern mining we use hidden markov model (HMM) along with tree mining algorithm.
A FRAMEWORK FOR SUMMARIZATION OF ONLINE OPINION USING WEIGHTING SCHEMEaciijournal
Recently there is wide use of social media includes various opinion sites, complaints sites, government
sites, question-answering sites, etc. through which customer get services, opinion, information, etc. but
because of this there is more and more use of these social media right now so huge amount of data will be
created, from this huge data people get confused while taking any decision about particular problem or
services. For example, customer wants to purchase a product at that time he/she want the previous
customer feedback or opinion about that product. But if there is lots of opinion available for particular
product then that customer get confused while taking decision whether purchase that product or not. In this
case there is a need of summarization concept means that only show the short and concise manner
summary about service or product so that customer or organization easily understand and able to take
right decision fast. Our proposed framework creating such summary which contain three main phases or
steps. Firstly preprocessing is done in that stop words are removed and stemming is performed. In second
phase identify frequent features using two techniques weight constraint and association rule and at the last
phase it find semantics and generate the summary so that customer will able to take step without confusion.
A FRAMEWORK FOR SUMMARIZATION OF ONLINE OPINION USING WEIGHTING SCHEMEaciijournal
Recently there is wide use of social media includes various opinion sites, complaints sites, government
sites, question-answering sites, etc. through which customer get services, opinion, information, etc. but
because of this there is more and more use of these social media right now so huge amount of data will be
created, from this huge data people get confused while taking any decision about particular problem or
services. For example, customer wants to purchase a product at that time he/she want the previous
customer feedback or opinion about that product. But if there is lots of opinion available for particular
product then that customer get confused while taking decision whether purchase that product or not. In this
case there is a need of summarization concept means that only show the short and concise manner
summary about service or product so that customer or organization easily understand and able to take
right decision fast. Our proposed framework creating such summary which contain three main phases or
steps. Firstly preprocessing is done in that stop words are removed and stemming is performed. In second
phase identify frequent features using two techniques weight constraint and association rule and at the last
phase it find semantics and generate the summary so that customer will able to take step without confusion.
Neural Network Based Context Sensitive Sentiment AnalysisEditor IJCATR
Social media communication is evolving more in these days. Social networking site is being rapidly increased in recent years, which provides platform to connect people all over the world and share their interests. The conversation and the posts available in social media are unstructured in nature. So sentiment analysis will be a challenging work in this platform. These analyses are mostly performed in machine learning techniques which are less accurate than neural network methodologies. This paper is based on sentiment classification using Competitive layer neural networks and classifies the polarity of a given text whether the expressed opinion in the text is positive or negative or neutral. It determines the overall topic of the given text. Context independent sentences and implicit meaning in the text are also considered in polarity classification.
CROWDSOURCING EMOTIONS IN MUSIC DOMAIN Erion Çano and Maurizio Morisio ijaia
An important source of intelligence for music emotion recognition today comes from user-provided community tags about songs or artists. Recent crowdsourcing approaches such as harvesting social tags, design of collaborative games and web services or the use of Mechanical Turk, are becoming popular in the literature. They provide a cheap, quick and efficient method, contrary to professional labeling of songs which is expensive and does not scale for creating large datasets. In this paper we discuss the viability of various crowdsourcing instruments providing examples from research works. We also share our own experience, illustrating the steps we followed using tags collected from Last.fm for the creation of two
music mood datasets which are rendered public. While processing affect tags of Last.fm, we observed that they tend to be biased towards positive emotions; the resulting dataset thus contain more positive songs than negative ones.
Finding The Voice of A Virtual Community of PracticeConnie White
Critical components for a successful Community of Practice (CoP) are that: 1) the community members have a space where their voice can be heard and that, (2) the proper technology is given to them to aid in this effort. We describe a Dynamic Delphi system under development which interprets the group’s voice in the creation of information during the initial start up phases when cultivating a CoP. Community members’ alternatives are explored, justified and debated over periods of time, and best reflect the group’s opinion at any moment in time where collective intelligence will be created from the interactions amongst group members. The system could handle a wide variety of types of decisions reflecting the diversity of goals given a CoP including emergency response actions, prediction markets, lobbying efforts, any sort of problem solving, making investment suggestions, etc. Pilot studies indicate that the group creates a greater number of better ideas. Ongoing studies are described, including applications to emergency management planning and response. They demonstrate that implementing a Dynamic Delphi system will prove conducive for building the initial repertoire of ideas, rules, policies or any other aspect of the community’s ‘voice’ that should be heard, in such a way that the individual voices are juxtaposed in harmony to create a single song.
User centered design assumes that a research phase with a representative sample of the final users should be the basis for the definition of the functional and soft requirements of a project. How can we translate the results of the ux research into actionable requirements?
In my talk, I wish to give you some suggestions on how to informally analyse the verbal results of the ux research to identify the schemata, the ontologies, the taxonomies and the functions of your application.
Online interview is not a new thing but in this covid-19 situation it seems to be the only option. However, assessing the candidate on a video call may not be that effective. Having an AI based Interview Assessment System could prove to be useful, which would take input as speech and will give output as detailed analysis of that speech. While most the research work currently done focuses only on finding sentiment or personality from speech, our system aims to extract multiple information from the speech and provide a detailed analysis. The analysis would include a detailed report containing results about confidence level of the person, his/her emotional state, speed of the speech, frequently repeated words and also personality reflected by that speech. An interview panel consists of various members focusing on different aspect of the answer given by the candidate, some focus on technical correctness while, some simply want to check the communication skills of the candidate. Having an AI system giving a report on the soft skills part would reduce the work for interviewer and he/she could give complete focus on the technical correctness of the answer. This could eventually help save time and resources used by organizations for hiring process. This intention of creating this system is to assist the interview process and give analysis report based on the speech input instead a giving a verdict about selection of the candidate. Thus, this system could use not only by the interviewers but also by the candidates. The output provided would be a detailed report which could prove to be a good feedback for the students who are preparing for the interview. Having a feedback would help candidates work on their week points and thus perform better in further interviews.
Generating domain specific sentiment lexicons using the Web Directory acijjournal
In this paper we aim at proposing a method to automatically build a sentiment lexicon which is domain based. There has been a demand for the construction of generated and labeled sentiment lexicon. For data on the social web (E.g., tweets), methods which make use of the synonymy relation don't work well, as we completely ignore the significance of terms belonging to specific domains. Here we propose to
generate a sentiment lexicon for any domain specified, using a twofold method. First we build sentiment scores using the micro-blogging data, and then we use these scores on the ontological structure provided by Open Directory Project [1], to build a custom sentiment lexicon for analyzing domain specific microblogging data.
Speaker specific feature based clustering and its applications in language in...IJECEIAES
Forensic speaker recognition (FSR) is the process of determining whether the source of a questioned voice recording (trace) is of a specific individual (suspected speaker). Most existing methods measure inter-utterance similarities directly based on spectrum-based characteristics, the resulting clusters may not be well related to speaker’s, but rather to different acoustic classes. This research addresses this deficiency by projecting languageindependent utterances into a reference space equipped to cover the standard voice features underlying the entire utterance set. Then a clustering approach is proposed based on the peak approximation in order to maximize the similarities between language-independent utterances within all clusters. This method uses a K-medoid, Fuzzy C-means, Gustafson and Kessel and Gath-Geva algorithm to evaluate the cluster to which each utterance should be allocated, overcoming the disadvantage of traditional hierarchical clustering that the ultimate outcome can only hit the optimum recognition efficiency. The recognition efficiency of K-medoid, Fuzzy C-means, Gustafson and Kessel and Gath-Geva clustering algorithms are 95.2%, 97.3%, 98.5% and 99.7% and EER are 3.62%, 2.91 %, 2.82%, and 2.61% respectively. The EER improvement of the Gath-Geva technique based FSRsystem compared with Gustafson and Kessel and Fuzzy C-means is 8.04% and 11.49% respectively.
A Text Mining Research Based on LDA Topic Modellingcsandit
A Large number of digital text information is gener
ated every day. Effectively searching,
managing and exploring the text data has become a m
ain task. In this paper, we first represent
an introduction to text mining and a probabilistic
topic model Latent Dirichlet allocation. Then
two experiments are proposed - Wikipedia articles a
nd users’ tweets topic modelling. The
former one builds up a document topic model, aiming
to a topic perspective solution on
searching, exploring and recommending articles. The
latter one sets up a user topic model,
providing a full research and analysis over Twitter
users’ interest. The experiment process
including data collecting, data pre-processing and
model training is fully documented and
commented. Further more, the conclusion and applica
tion of this paper could be a useful
computation tool for social and business research.
The peer-reviewed International Journal of Engineering Inventions (IJEI) is started with a mission to encourage contribution to research in Science and Technology. Encourage and motivate researchers in challenging areas of Sciences and Technology.
A FILM SYNOPSIS GENRE CLASSIFIER BASED ON MAJORITY VOTEkevig
We propose an automatic classification system of movie genres based on different features from their textual
synopsis. Our system is first trained on thousands of movie synopsis from online open databases, by learning relationships between textual signatures and movie genres. Then it is tested on other movie synopsis,
and its results are compared to the true genres obtained from the Wikipedia and the Open Movie Database
(OMDB) databases. The results show that our algorithm achieves a classification accuracy exceeding 75%.
The community detection in complex networks has attracted a growing interest and is the subject of several
researches that have been proposed to understand the network structure and analyze the network
properties. In this paper, we give a thorough overview of different community discovery strategies, we
propose taxonomy of these methods, and we specify the differences between the suggested classes which
helping designers to compare and choose the most suitable strategy for the various types of network
encountered in the real world.
A FILM SYNOPSIS GENRE CLASSIFIER BASED ON MAJORITY VOTEijnlc
We propose an automatic classification system of movie genres based on different features from their textual synopsis. Our system is first trained on thousands of movie synopsis from online open databases, by learning relationships between textual signatures and movie genres. Then it is tested on other movie synopsis, and its results are compared to the true genres obtained from the Wikipedia and the Open Movie Database
(OMDB) databases. The results show that our algorithm achieves a classification accuracy exceeding 75%.
Extracting frequent pattern from Human Interaction in Meeting using Tree base...ijcax
Human Interaction in meetings is one of the famous fields of social dynamics. Meeting is integral part of
every organization. In this, meeting outcome is extracted using tree based approach. Meetings contents or
conversation are available in forms such as audio, video and text. In this, pattern of meeting is extracted
from text document. An interaction is represented in the form of tree. Meeting Output is generated using
data mining technique. Firstly the contents are filtered, extracted and steamed. Secondly classification is
done into six categories propose, comment, acknowledgement, request Info, ask Opinion, pos Opinion, and
neg Opinion. Next the interaction tree is constructed which represent the interaction flow of meeting.
Finally the meeting output is generated from interaction tree using frequent pattern mining algorithm. The
behavior of person is determined which includes a person who proposed a lot of ideas, a person with
positive or negative attitude.
Tree Based Mining for Discovering Patterns of Human Interactions in MeetingsIJERA Editor
Meetings are an integral part of workplace dynamics also an important communication and coordination activity of teams: statuses are discussed, decisions, alternatives are considered, details are explained and ideas are generated. In this work, data mining techniques to detect and analyze frequent interaction patterns. We look forward to discover various types of new knowledge on interactions. An interaction tree pattern mining algorithms was proposed to analyze tree structures and extract interaction flow patterns. In this paper we propose the tree based mining for human interaction flow in a discussion session is represented as a tree. In this work we extend an interaction tree mining algorithm in three ways. First, we propose a mining method to extract frequent patterns of human interaction. Second, we explore embedded sub tree mining for hidden interaction pattern discovery. Third, we propose temporal data mining techniques for extracting the temporal patterns from the captured content of time series of different meetings in particular time periods such as month or year. Because of the human integration activities varied based on time and experience of events. For extracting temporal pattern mining we use hidden markov model (HMM) along with tree mining algorithm.
A FRAMEWORK FOR SUMMARIZATION OF ONLINE OPINION USING WEIGHTING SCHEMEaciijournal
Recently there is wide use of social media includes various opinion sites, complaints sites, government
sites, question-answering sites, etc. through which customer get services, opinion, information, etc. but
because of this there is more and more use of these social media right now so huge amount of data will be
created, from this huge data people get confused while taking any decision about particular problem or
services. For example, customer wants to purchase a product at that time he/she want the previous
customer feedback or opinion about that product. But if there is lots of opinion available for particular
product then that customer get confused while taking decision whether purchase that product or not. In this
case there is a need of summarization concept means that only show the short and concise manner
summary about service or product so that customer or organization easily understand and able to take
right decision fast. Our proposed framework creating such summary which contain three main phases or
steps. Firstly preprocessing is done in that stop words are removed and stemming is performed. In second
phase identify frequent features using two techniques weight constraint and association rule and at the last
phase it find semantics and generate the summary so that customer will able to take step without confusion.
A FRAMEWORK FOR SUMMARIZATION OF ONLINE OPINION USING WEIGHTING SCHEMEaciijournal
Recently there is wide use of social media includes various opinion sites, complaints sites, government
sites, question-answering sites, etc. through which customer get services, opinion, information, etc. but
because of this there is more and more use of these social media right now so huge amount of data will be
created, from this huge data people get confused while taking any decision about particular problem or
services. For example, customer wants to purchase a product at that time he/she want the previous
customer feedback or opinion about that product. But if there is lots of opinion available for particular
product then that customer get confused while taking decision whether purchase that product or not. In this
case there is a need of summarization concept means that only show the short and concise manner
summary about service or product so that customer or organization easily understand and able to take
right decision fast. Our proposed framework creating such summary which contain three main phases or
steps. Firstly preprocessing is done in that stop words are removed and stemming is performed. In second
phase identify frequent features using two techniques weight constraint and association rule and at the last
phase it find semantics and generate the summary so that customer will able to take step without confusion.
Neural Network Based Context Sensitive Sentiment AnalysisEditor IJCATR
Social media communication is evolving more in these days. Social networking site is being rapidly increased in recent years, which provides platform to connect people all over the world and share their interests. The conversation and the posts available in social media are unstructured in nature. So sentiment analysis will be a challenging work in this platform. These analyses are mostly performed in machine learning techniques which are less accurate than neural network methodologies. This paper is based on sentiment classification using Competitive layer neural networks and classifies the polarity of a given text whether the expressed opinion in the text is positive or negative or neutral. It determines the overall topic of the given text. Context independent sentences and implicit meaning in the text are also considered in polarity classification.
CROWDSOURCING EMOTIONS IN MUSIC DOMAIN Erion Çano and Maurizio Morisio ijaia
An important source of intelligence for music emotion recognition today comes from user-provided community tags about songs or artists. Recent crowdsourcing approaches such as harvesting social tags, design of collaborative games and web services or the use of Mechanical Turk, are becoming popular in the literature. They provide a cheap, quick and efficient method, contrary to professional labeling of songs which is expensive and does not scale for creating large datasets. In this paper we discuss the viability of various crowdsourcing instruments providing examples from research works. We also share our own experience, illustrating the steps we followed using tags collected from Last.fm for the creation of two
music mood datasets which are rendered public. While processing affect tags of Last.fm, we observed that they tend to be biased towards positive emotions; the resulting dataset thus contain more positive songs than negative ones.
Finding The Voice of A Virtual Community of PracticeConnie White
Critical components for a successful Community of Practice (CoP) are that: 1) the community members have a space where their voice can be heard and that, (2) the proper technology is given to them to aid in this effort. We describe a Dynamic Delphi system under development which interprets the group’s voice in the creation of information during the initial start up phases when cultivating a CoP. Community members’ alternatives are explored, justified and debated over periods of time, and best reflect the group’s opinion at any moment in time where collective intelligence will be created from the interactions amongst group members. The system could handle a wide variety of types of decisions reflecting the diversity of goals given a CoP including emergency response actions, prediction markets, lobbying efforts, any sort of problem solving, making investment suggestions, etc. Pilot studies indicate that the group creates a greater number of better ideas. Ongoing studies are described, including applications to emergency management planning and response. They demonstrate that implementing a Dynamic Delphi system will prove conducive for building the initial repertoire of ideas, rules, policies or any other aspect of the community’s ‘voice’ that should be heard, in such a way that the individual voices are juxtaposed in harmony to create a single song.
User centered design assumes that a research phase with a representative sample of the final users should be the basis for the definition of the functional and soft requirements of a project. How can we translate the results of the ux research into actionable requirements?
In my talk, I wish to give you some suggestions on how to informally analyse the verbal results of the ux research to identify the schemata, the ontologies, the taxonomies and the functions of your application.
With the rapidly increasing growth in the field of internet and web usage, it has become essential to use a certain specific powerful tool, which should be capable to analyze and rank all these available reviews/opinion on the web/Internet. In this paper we have propose a new and effective approach which uses a powerful sentiment analysis procedure which will be based on an ontological adjustment and arrangements. This study also aims to understand pos tag order to get detailed observation for any review or opinion, it also helps in identifying all present positive /Negative sentiments and suggest a proper sentence inclination. For this we have used reviews available on internet regarding Nokia and Stanford parser for the purpose or pos tagging.
The goal of this project is to build a classifier able to predict whether a song is happy or sad analysing its lyrics. Most of the research on music classication is based on features
obtained by audio signals. However, the exploration of lyrics alone as a source of information can be relevant in music
classication. It is an interesting problem and it has not been widely explored in the literature.
Similar to Extracting frequent pattern from Human Interaction in Meeting using Tree based Approach (20)
NEW ONTOLOGY RETRIEVAL IMAGE METHOD IN 5K COREL IMAGESijcax
Semantic annotation of images is an important research topic on both image understanding and database
or web image search. Image annotation is a technique to choosing appropriate labels for images with
extracting effective and hidden feature in pictures. In the feature extraction step of proposed method, we
present a model, which combined effective features of visual topics (global features over an image) and
regional contexts (relationship between the regions in Image and each other regions images) to automatic
image annotation.In the annotation step of proposed method, we create a new ontology (base on WordNet
ontology) for the semantic relationships between tags in the classification and improving semantic gap
exist in the automatic image annotation.Experiments result on the 5k Corel dataset show the proposed
method of image annotation in addition to reducing the complexity of the classification, increased accuracy
compared to the another methods
THE STUDY OF CUCKOO OPTIMIZATION ALGORITHM FOR PRODUCTION PLANNING PROBLEMijcax
Constrained Nonlinear programming problems are hard problems, and one of the most widely used and
common problems for production planning problem to optimize. In this study, one of the mathematical
models of production planning is survey and the problem solved by cuckoo algorithm. Cuckoo Algorithm is
efficient method to solve continues non linear problem. Moreover, mentioned models of production
planning solved with Genetic algorithm and Lingo software and the results will compared. The Cuckoo
Algorithm is suitable choice for optimization in convergence of solution
COMPARATIVE ANALYSIS OF ROUTING PROTOCOLS IN MOBILE AD HOC NETWORKSijcax
A Mobile Ad Hoc Network (MANET) is a collection of mobile nodes that want to communicate without any
pre-determined infrastructure and fixed organization of available links. Each node in MANET operates as
a router, forwarding information packets for other mobile nodes. There are many routing protocols that
possess different performance levels in different scenarios. The main task is to evaluate the existing routing
protocols and finding by comparing them the best one. In this article we compare AODV, DSR, DSDV,
OLSR and DYMO routing protocols in mobile ad hoc networks (MANETs) to specify the best operational
conditions for each MANETs protocol. We study these five MANETs routing protocols by different
simulations in NS-2 simulator. We describe that pause time parameter affect their performance. This
performance analysis is measured in terms of Packet Delivery Ratio, Average End-to-End Delay,
Normalized Routing Load and Average Throughput.
PREDICTING ACADEMIC MAJOR OF STUDENTS USING BAYESIAN NETWORKS TO THE CASE OF ...ijcax
In this study, which took place current year in the city of Maragheh in IRAN. Number of high school
students in the fields of study: mathematics, Experimental Sciences, humanities, vocational, business and
science were studied and compared. The purpose of this research is to predict the academic major of high
school students using Bayesian networks. The effective factors have been used in academic major selection
for the first time as an effective indicator of Bayesian networks. Evaluation of Impacts of indicators on
each other, discretization data and processing them was performed by GeNIe. The proper course would be
advised for students to continue their education.
A Multi Criteria Decision Making Based Approach for Semantic Image Annotation ijcax
Automatic image annotation has emerged as an important research topic due to its potential application on
both image understanding and web image search. This paper presents a model, which integrates visual
topics and regional contexts to automatic image annotation. Regional contexts model the relationship
between the regions, while visual topics provide the global distribution of topics over an image. Previous
image annotation methods neglected the relationship between the regions in an image, while these regions
are exactly explanation of the image semantics, therefore considering the relationship between them are
helpful to annotate the images. Regional contexts and visual topics are learned by PLSA (Probability
Latent Semantic Analysis) from the training data. The proposed model incorporates these two types of
information by MCDM (Multi Criteria Decision Making) approach based on WSM (Weighted Sum
Method). Experiments conducted on the 5k Corel dataset demonstrate the effectiveness of the proposed
model.
On Fuzzy Soft Multi Set and Its Application in Information Systems ijcax
Research on information and communication technologies have been developed rapidly since it can be
applied easily to several areas like computer science, medical science, economics, environments,
engineering, among other. Applications of soft set theory, especially in information systems have been
found paramount importance. Recently, Mukherjee and Das defined some new operations in fuzzy soft
multi set theory and show that the De-Morgan’s type of results hold in fuzzy soft multi set theory with
respect to these newly defined operations. In this paper, we extend their work and study some more basic
properties of their defined operations. Also, we define some basic supporting tools in information system
also application of fuzzy soft multi sets in information system are presented and discussed. Here we define
the notion of fuzzy multi-valued information system in fuzzy soft multi set theory and show that every fuzzy
soft multi set is a fuzzy multi valued information system.
Web is a collection of inter-related files on one or more web servers while web mining means extracting
valuable information from web databases. Web mining is one of the data mining domains where data
mining techniques are used for extracting information from the web servers. The web data includes web
pages, web links, objects on the web and web logs. Web mining is used to understand the customer
behaviour, evaluate a particular website based on the information which is stored in web log files. Web
mining is evaluated by using data mining techniques, namely classification, clustering, and association
rules. It has some beneficial areas or applications such as Electronic commerce, E-learning, Egovernment, E-policies, E-democracy, Electronic business, security, crime investigation and digital library.
Retrieving the required web page from the web efficiently and effectively becomes a challenging task
because web is made up of unstructured data, which delivers the large amount of information and increase
the complexity of dealing information from different web service providers. The collection of information
becomes very hard to find, extract, filter or evaluate the relevant information for the users. In this paper,
we have studied the basic concepts of web mining, classification, processes and issues. In addition to this,
this paper also analyzed the web mining research challenges.
SPAM FILTERING SECURITY EVALUATION FRAMEWORK USING SVM, LR AND MILR ijcax
The Pattern classification system classifies the pattern into feature space within a boundary. In case
adversarial applications use, for example Spam Filtering, the Network Intrusion Detection System (NIDS),
Biometric Authentication, the pattern classification systems are used. Spam filtering is an adversary
application in which data can be employed by humans to attenuate perspective operations. To appraise the
security issue related Spam Filtering voluminous machine learning systems. We presented a framework for
the experimental evaluation of the classifier security in an adversarial environments, that combines and
constructs on the arms race and security by design, Adversary modelling and Data distribution under
attack. Furthermore, we presented a SVM, LR and MILR classifier for classification to categorize email as
legitimate (ham) or spam emails on the basis of thee text samples.
Visually impaired people face many problems in their day to day lives. Among them, outdoor navigation is
one of the major concerns. The existing solutions based on Wireless Sensor Networks(WSN) and Global
Positioning System (GPS) track ZigBee units or RFID (Radio Frequency Identification) tags fixed on the
navigation system. The issues pertaining to these solutions are as follows: (1) It is suitable only when the
visually impaired person is commuting in a familiar environment; (2) The device provides only a one way
communication; (3) Most of these instruments are heavy and sometimes costly. Preferable solution would
be to make a system which is easy to carry and cheap.
The objective of this paper is to break down the technological barriers, and to propose a system by
developing an Android App which would help a visually impaired person while traveling via the public
transport system like Bus. The proposed system uses an inbuilt feature of smart phone such as GPS
location tracker to track the location of the user and Text to Speech converter. The system also integrates
Google Speech to Text converter for capturing the voice input and converts them to text. This system
recommends the requirement of installing a GPS module in buses for real time tracking. With minor
modification, this App can also help older people for independent navigation.
INTELLIGENT AGENT FOR PUBLICATION AND SUBSCRIPTION PATTERN ANALYSIS OF NEWS W...ijcax
The rapid growth of Internet has revolutionized online news reporting. Many users tend to use online news
websites to obtain news information. When considering Sri Lanka, there are numerous news websites,
which are subscribed on a daily basis. With the rise in this number of news websites, the Sri Lankan
authorities of media face the issue of lacking a proper methodology or a tool which is capable of tracking
and regulating publications made by different disseminators of news.
This paper proposes a News Agent toolbox which periodically extracts news articles and associated
comments with the aid of a concept called Mapping Rules; to classify them into Personalized Categories
defined in terms of keywords based Category Profiles. The proposed tool also analyzes comments made by
the readers with the aid of simple statistical techniques to discover the most popular news articles and
fluctuations in popularity of news stories.
ADVANCED E-VOTING APPLICATION USING ANDROID PLATFORMijcax
The advancement in the mobile devices, wireless and web technologies given rise to the new application
that will make the voting process very easy and efficient. The E-voting promises the possibility of
convenient, easy and safe way to capture and count the votes in an election[1]. This research project
provides the specification and requirements for E-Voting using an Android platform. The e-voting means
the voting process in election by using electronic device. The android platform is used to develop an evoting application. At first, an introduction about the system is presented. Sections II and III describe all
the concepts (survey, design and implementation) that would be used in this work. Finally, the proposed evoting system will be presented. This technology helps the user to cast the vote without visiting the polling
booth. The application follows proper authentication measures in order to avoid fraud voters using the
system. Once the voting session is completed the results can be available within a fraction of seconds. All
the candidates vote count is encrypted and stored in the database in order to avoid any attacks and
disclosure of results by third person other than the administrator. Once the session is completed the admin
can decrypt the vote count and publish results and can complete the voting process.
The design of silicon chips in every semiconductor industry involves the testing of these chips with other
components on the board. The platform developed acts as power on vehicle for the silicon chips. This
Printed Circuit Board design that serves as a validation platform is foundational to the semiconductor
industry.
The manual/repetitive design activities that accompany the development of this board must be minimized to
achieve high quality, improve design efficiency, and eliminate human-errors. One of the time consuming
tasks in the board design is the Trace Length matching. The paper aims to reduce the length matching time
by automating it using SKILL scripts.
RESEARCH TRENDS İN EDUCATIONAL TECHNOLOGY İN TURKEY: 2010-2018 YEAR THESIS AN...ijcax
The purpose of this research is the analysis using meta-analysis of studies in the field of Educational
Technology in Turkey and in the field is to demonstrate how to get to that trend. For this purpose, a total of
263 studies were analyzed including 98 theses and 165 articles published between 2010-2018. Purpose
sampling method was used when selecting publications. In the research, while selecting articles and theses;
Turkey addressed; YOK Tez Tarama Database, Journal of Hacettepe University Faculty of Education,
Educational Sciences : Theory & Practice Journal, Education and Science Journal, Elementary Education
Online Journal, The Turkish Online Journal of Education and The Turkish Online Journal of Educational
Technology used in journals. Publications have been reviewed under 11 criteria. Index, year of
publication, research scope, method, education level, sample, number of samples, data collection methods,
analysis techniques, and research tendency, research topics in Educational Technology Research in Turkey
has revealed. The data is interpreted based on percentage and frequency and the results are shown using
the table.
RESEARCH TRENDS İN EDUCATIONAL TECHNOLOGY İN TURKEY: 2010-2018 YEAR THESIS AN...ijcax
The purpose of this research is the analysis using meta-analysis of studies in the field of Educational
Technology in Turkey and in the field is to demonstrate how to get to that trend. For this purpose, a total of
263 studies were analyzed including 98 theses and 165 articles published between 2010-2018. Purpose
sampling method was used when selecting publications. In the research, while selecting articles and theses;
Turkey addressed; YOK Tez Tarama Database, Journal of Hacettepe University Faculty of Education,
Educational Sciences : Theory & Practice Journal, Education and Science Journal, Elementary Education
Online Journal, The Turkish Online Journal of Education and The Turkish Online Journal of Educational
Technology used in journals. Publications have been reviewed under 11 criteria. Index, year of
publication, research scope, method, education level, sample, number of samples, data collection methods,
analysis techniques, and research tendency, research topics in Educational Technology Research in Turkey
has revealed. The data is interpreted based on percentage and frequency and the results are shown using
the table
IMPACT OF APPLYING INTERNATIONAL QUALITY STANDARDS ON MEDICAL EQUIPMENT IN SA...ijcax
With the great development that, modern medical technology is witnessing today, medical devices and
equipment have become a basic pillar of any healthcare system in the world and cannot be dispensed with,
so we find competition between the major companies that manufacture medical devices and equipment
resulting in a huge variety of complex modern medical technologies. These medical devices and equipment
require high accuracy in manufacturing and packaging in addition to operation, maintenance, and followup, because any error in any of the previous stages will have bad consequences for the patients and the
health system, there are many accidents that have led to some deaths. Therefore, we find that many medical
device producers and medical companies in addition to health service providers seek to find systems and
protocols to reduce accidents resulting from medical devices. As a result, many systems have recently
appeared that seek to protect from the dangers of medical devices and equipment. This research aims to
conduct a study of the effects of international standards on the safety of medical devices and equipment
and reduce their risks. By counting the international standards in force in the Kingdom of Saudi Arabia
that are applied by the Saudi Food and Drug Authority, making questionnaires, and distributing them to
health service providers and regulatory bodies for medical devices and equipment, considering the data,
these data will be analysed and evaluated the effectiveness of quality systems and standards in maintaining
Effectiveness and quality of medical devices and equipment. The study will include governmental and
private health services sectors.
SPAM FILTERING SECURITY EVALUATION FRAMEWORK USING SVM, LR AND MILR ijcax
The Pattern classification system classifies the pattern into feature space within a boundary. In case adversarial applications use, for example Spam Filtering, the Network Intrusion Detection System (NIDS), Biometric Authentication, the pattern classification systems are used. Spam filtering is an adversary
application in which data can be employed by humans to attenuate perspective operations. To appraise the
security issue related Spam Filtering voluminous machine learning systems. We presented a framework for the experimental evaluation of the classifier security in an adversarial environments, that combines and constructs on the arms race and security by design, Adversary modelling and Data distribution under
attack. Furthermore, we presented a SVM, LR and MILR classifier for classification to categorize email as legitimate (ham) or spam emails on the basis of thee text samples
Developing Product Configurator Tool Using CADs’ API with the help of Paramet...ijcax
Order placingis a crucial phase of lifecycle of a Mass-customizable product and seeks improvement in
Mechanical industry. ‘Product Configurator’ is a good solution to bring in data transparency and speed
up the process. Configuration tools arebeing used on a very small scale,reasons being lack of awareness
and dearer costs of existing tools. In this research work a product configurator is developedfor
Hydraulic Actuator (HA).This method uses Applicable Programing Interface (API) of a CAD tool coupled
with Visual Basics (VB) and MS Excel.Itis a standaloneapplication of VB and its integration into web
portal can be the future scope. The final aim was to reduce time delay at CRM phase,bring more
transparency in the ordering system and to establish a method which, small and medium scale enterprises
canafford. Trails on the tool developed generated Part-Assembly drawings, BOM and JT files in
moments.
DESIGN AND DEVELOPMENT OF CUSTOM CHANGE MANAGEMENT WORKFLOW TEMPLATES AND HAN...ijcax
A large no. of automobile companies finding a convinient way to manage design changes with the use of
various PLM techniques. Change in any product is something that should occur on timely basis to match
up with customer requirement and cost reduction. The change made in the vehicle designs directly affects
various concerned agencies. Automobile Vehicle structures contains thousands of parts and if there is any
change is occurring in child parts then it becomes important to track that impacted part, propose a solution
on that part and release a new assembly structure with feasible changes such that all efforts need to be
done for cost reduction.
Visually impaired people face many problems in their day to day lives. Among them, outdoor navigation is
one of the major concerns. The existing solutions based on Wireless Sensor Networks(WSN) and Global
Positioning System (GPS) track ZigBee units or RFID (Radio Frequency Identification) tags fixed on the
navigation system. The issues pertaining to these solutions are as follows: (1) It is suitable only when the
visually impaired person is commuting in a familiar environment; (2) The device provides only a one way
communication; (3) Most of these instruments are heavy and sometimes costly. Preferable solution would
be to make a system which is easy to carry and cheap.
The objective of this paper is to break down the technological barriers, and to propose a system by
developing an Android App which would help a visually impaired person while traveling via the public
transport system like Bus. The proposed system uses an inbuilt feature of smart phone such as GPS
location tracker to track the location of the user and Text to Speech converter. The system also integrates
Google Speech to Text converter for capturing the voice input and converts them to text. This system
recommends the requirement of installing a GPS module in buses for real time tracking. With minor
modification, this App can also help older people for independent navigation.
TEACHER’S ATTITUDE TOWARDS UTILISING FUTURE GADGETS IN EDUCATION ijcax
Today’s era is an era of modernization and globalization. Everything is happening at a very fast rate
whether it is politics, societal reforms, commercialization, transportation, or educational innovations. In
every few second, technology grows either in the form of arrival of the new devices/gadgets with millions of
apps and these latest technological objects may be in the form of hardware/software devices. We are the
educationists, teachers, students and stakeholders of present Indian educational system. These
gadgets/devices are partly being used by us or most of them are still unaware of these innovative
technologies due to the mass media or economical factor. So, there is a need to improvise ourselves
towards utilizing the future gadgets in order to explore the educational uses, barriers and preparatoryneeds of these available devices for educational purposes. This paper aims to study the opinion of the
teacher-educators about the usage of future gadgets in higher education. It will also contribute towards
establishing the list of latest technological devices, and how it can enhances the process of teachinglearning system.
Safalta Digital marketing institute in Noida, provide complete applications that encompass a huge range of virtual advertising and marketing additives, which includes search engine optimization, virtual communication advertising, pay-per-click on marketing, content material advertising, internet analytics, and greater. These university courses are designed for students who possess a comprehensive understanding of virtual marketing strategies and attributes.Safalta Digital Marketing Institute in Noida is a first choice for young individuals or students who are looking to start their careers in the field of digital advertising. The institute gives specialized courses designed and certification.
for beginners, providing thorough training in areas such as SEO, digital communication marketing, and PPC training in Noida. After finishing the program, students receive the certifications recognised by top different universitie, setting a strong foundation for a successful career in digital marketing.
Exploiting Artificial Intelligence for Empowering Researchers and Faculty, In...Dr. Vinod Kumar Kanvaria
Exploiting Artificial Intelligence for Empowering Researchers and Faculty,
International FDP on Fundamentals of Research in Social Sciences
at Integral University, Lucknow, 06.06.2024
By Dr. Vinod Kumar Kanvaria
Macroeconomics- Movie Location
This will be used as part of your Personal Professional Portfolio once graded.
Objective:
Prepare a presentation or a paper using research, basic comparative analysis, data organization and application of economic information. You will make an informed assessment of an economic climate outside of the United States to accomplish an entertainment industry objective.
How to Make a Field invisible in Odoo 17Celine George
It is possible to hide or invisible some fields in odoo. Commonly using “invisible” attribute in the field definition to invisible the fields. This slide will show how to make a field invisible in odoo 17.
June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...Levi Shapiro
Letter from the Congress of the United States regarding Anti-Semitism sent June 3rd to MIT President Sally Kornbluth, MIT Corp Chair, Mark Gorenberg
Dear Dr. Kornbluth and Mr. Gorenberg,
The US House of Representatives is deeply concerned by ongoing and pervasive acts of antisemitic
harassment and intimidation at the Massachusetts Institute of Technology (MIT). Failing to act decisively to ensure a safe learning environment for all students would be a grave dereliction of your responsibilities as President of MIT and Chair of the MIT Corporation.
This Congress will not stand idly by and allow an environment hostile to Jewish students to persist. The House believes that your institution is in violation of Title VI of the Civil Rights Act, and the inability or
unwillingness to rectify this violation through action requires accountability.
Postsecondary education is a unique opportunity for students to learn and have their ideas and beliefs challenged. However, universities receiving hundreds of millions of federal funds annually have denied
students that opportunity and have been hijacked to become venues for the promotion of terrorism, antisemitic harassment and intimidation, unlawful encampments, and in some cases, assaults and riots.
The House of Representatives will not countenance the use of federal funds to indoctrinate students into hateful, antisemitic, anti-American supporters of terrorism. Investigations into campus antisemitism by the Committee on Education and the Workforce and the Committee on Ways and Means have been expanded into a Congress-wide probe across all relevant jurisdictions to address this national crisis. The undersigned Committees will conduct oversight into the use of federal funds at MIT and its learning environment under authorities granted to each Committee.
• The Committee on Education and the Workforce has been investigating your institution since December 7, 2023. The Committee has broad jurisdiction over postsecondary education, including its compliance with Title VI of the Civil Rights Act, campus safety concerns over disruptions to the learning environment, and the awarding of federal student aid under the Higher Education Act.
• The Committee on Oversight and Accountability is investigating the sources of funding and other support flowing to groups espousing pro-Hamas propaganda and engaged in antisemitic harassment and intimidation of students. The Committee on Oversight and Accountability is the principal oversight committee of the US House of Representatives and has broad authority to investigate “any matter” at “any time” under House Rule X.
• The Committee on Ways and Means has been investigating several universities since November 15, 2023, when the Committee held a hearing entitled From Ivory Towers to Dark Corners: Investigating the Nexus Between Antisemitism, Tax-Exempt Universities, and Terror Financing. The Committee followed the hearing with letters to those institutions on January 10, 202
Embracing GenAI - A Strategic ImperativePeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
Biological screening of herbal drugs: Introduction and Need for
Phyto-Pharmacological Screening, New Strategies for evaluating
Natural Products, In vitro evaluation techniques for Antioxidants, Antimicrobial and Anticancer drugs. In vivo evaluation techniques
for Anti-inflammatory, Antiulcer, Anticancer, Wound healing, Antidiabetic, Hepatoprotective, Cardio protective, Diuretics and
Antifertility, Toxicity studies as per OECD guidelines
A Strategic Approach: GenAI in EducationPeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
Acetabularia Information For Class 9 .docxvaibhavrinwa19
Acetabularia acetabulum is a single-celled green alga that in its vegetative state is morphologically differentiated into a basal rhizoid and an axially elongated stalk, which bears whorls of branching hairs. The single diploid nucleus resides in the rhizoid.
2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasn’t one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
2024.06.01 Introducing a competency framework for languag learning materials ...
Extracting frequent pattern from Human Interaction in Meeting using Tree based Approach
1. International Journal of Computer-Aided technologies (IJCAx) Vol.1,No.2/3,October 2014
17
Extracting frequent pattern from Human
Interaction in Meeting using Tree based Approach
Prashant Puri and Kirti Korabu
Department of Information Technology, Sinhgad College of Engineering, Pune,India
Abstract
Human Interaction in meetings is one of the famous fields of social dynamics. Meeting is integral part of
every organization. In this, meeting outcome is extracted using tree based approach. Meetings contents or
conversation are available in forms such as audio, video and text. In this, pattern of meeting is extracted
from text document. An interaction is represented in the form of tree. Meeting Output is generated using
data mining technique. Firstly the contents are filtered, extracted and steamed. Secondly classification is
done into six categories propose, comment, acknowledgement, request Info, ask Opinion, pos Opinion, and
neg Opinion. Next the interaction tree is constructed which represent the interaction flow of meeting.
Finally the meeting output is generated from interaction tree using frequent pattern mining algorithm. The
behavior of person is determined which includes a person who proposed a lot of ideas, a person with
positive or negative attitude.
Keywords
Social Dynamics, Stop words, Frequency based Classification, Frequent Pattern Mining, Human
Interaction In Meetings
1.Introduction
Group social dynamics is one of the important areas in the field of research. Human interaction in
meeting is one of the important characteristics of group dynamics. Group social dynamics is
important for understanding the nature of meeting or understanding how conclusion was reached
Meetings are important for purpose of information exchange, problem solving, knowledge
sharing and creation. Meetings content a large amount of social and communication information.
Study of meetings explores the social behavior of participants in meetings which help us to
understand the conclusion of meetings, whether all members agreed on outcome, who did not
give opinion, who spoke little or lot. Extracted information from meetings is useful to predict the
human interaction which is useful for meetings participants, meeting organizer, meeting sponsor.
In this paper, techniques for extracting information from meeting to predict the human interaction
are discussed. Meeting contents are available in three forms audio, video and text which is used to
predict the human interactions. To predict the human interaction feature extraction and
classification of extracted feature is done. Feature extraction, classification, construction of
interaction tree and determine frequent pattern for meeting are discussed in this paper on basis of
text data.
2. International Journal of Computer-Aided technologies (IJCAx) Vol.1,No.2/3,October 2014
18
The remainder of this paper is organized as follows. Section II discusses related work. Section III
discussed the implementation of system. Section IV explores some applications. Finally, we
conclude the paper in Section V.
2.Related Work
Various researches have been conducted on discovering knowledge about human actions by
applying the concept of data mining. Casas-Garriga [3] proposed algorithms to mine unbounded
episodes from a sequence of events. The work is used to extract frequent episodes, i.e.,
collections of events occurring frequently together. Morita [5] proposed a pattern mining method
for the interpretation of human interactions in a poster exhibition. It extracts simultaneously
occurring patterns of primitive actions such as gaze and speech.I.McCowan[2] proposed the
technique to detect the group level interest in meetings.Zhiwen Yu[6] adopted a multimodal
method to infer human interaction based on a variety of features, such as speech tone, speaking
time, interaction occasion, gestures, attention and information about the previous session. Four
kinds of classification models, Support Vector Machine (SVM) uses LIBSVM, Bayesian Net,
Naive Bayes, and Decision Trees [9] are selected to infer the type of each interaction. The results
show that SVM is most appropriate and achieves a recognition rate of approximately 80 percent
[1]. Please refer to the earlier paper [7] for details about the human interaction recognition.
Zhiwen Yu proposed a tree base mining method that discovers patterns of human interaction in
meetings [8]. Garg[4] proposed an approach to recognize participant roles in meetings.
3.Implementations of System
In this system, the meeting output is predicted form conversation of the participants. The
conversations of participants are input to the system as text file. To predict the output flow of the
meeting is identify and from the flow interaction tree is constructed. A frequent pattern mining
algorithm is used to extract the output of the meeting. Also the meeting behavior and person
behavior is determined from the system. To extract the content of meeting following are the
measure steps
1. Extraction
2. Classification
3. Designing the Interaction tree.
4. Determining the meeting Output.
3. International Journal of Computer-Aided technologies (IJCAx) Vol.1,No.2/3,October 2014
19
3.1EXTRACTION
In this step, contents of the meeting are filter to remove the stop words from statements in text
file that contains the conversation. After removal of stop words, the steaming is performed to
classify the words or phrase to the particular category.
a.Stop Word :- These are the words that some users leave out of an statement. By dropping stop
words from an statement, the index size can typically be reduced by as much as 30% for a word
level index. A stop word typically is a word which doesn't contain much "informational"content.
For example, some example stop words are: "and", "the", "of", "it", "as", etc.
Eg : Statement before removing stop word
I think we should stage a concert to raise money.
After Extarction: * think * * stage * concert * raise money.
Here I, we, should,a and to is removed form statement.
b.Stemming :- A stemming is a process of linguistic normalization, in which the variant forms of
a word are reduced to a common form, for example,
Connection
Connections
Connective ---> connect
Connected
Document
Extraction
Classification
InteractionTree
MeetingOutput
4. International Journal of Computer-Aided technologies (IJCAx) Vol.1,No.2/3,October 2014
20
3.2CLASSIFICATION
Classification Input to classification is filtered words from extraction. The extracted words from
setp1 are classified into following categories propose, comment, Query, ask Opinion, pos
Opinion, neg Opinion and acknowledgement. Classification is done using frequency based
classification algorithm. Under each category there is list of word if word exits in a statement, the
given statement is classified to a category to which that word belong.
e.g1: Concerts take too long to organize.
As “too long” is negative phrase this statement will come under negative category.
e.g2: Yes tweets are very famous.
As “Yes” is positive word this statement will come under positive category.
3.3 DESIGNING THE INTERACTION TREE
In this, flow of conversation is determined. The flow is identified once the interaction tree is
constructed using the output of the classification step. This step will give the exact flow of
interaction in the meeting and attitude of participants in the meeting. Tree will be constructed
according to the following process.
1st
statement Elena: I think we should stage a concert to raise money. As it is a first
statement, it is proposed statement. Here Pro (E) means Propose by Elena
2nd
statement Lucas@Elena: Concerts take too long to organize. Let us have a bakesale. Here
Lucas@Elena means lucas reply to elena. As it is again a proposed statement and reply to first
this statement will child of first. So the tree will be as follow
3rd
statement Barbara@Elena: My cousin is in a band called The Tweets that might play for
free. Here Barbara response to Elena. As it is a positive response to 1st
statement, it will be other
child to first.
Pro
(E)
Pro
(E)
Pro
(L)
5. International Journal of Computer-Aided technologies (IJCAx) Vol.1,No.2/3,October 2014
21
3.4 MEETING OUTPUT-
The interaction tree is used to generate the meeting output. A frequent pattern mining algorithm is
used to extract the frequent pattern from a tree generated from meeting interaction. A pattern is
frequent trees or subtrees in the tree database. Following is the algorithm to find frequent tree and
subtree.
Algorithm 1. fitm (TD, α) (Frequent interaction tree pattern mining)
Input: a tree database TD and a support threshold α
Output: all frequent tree patterns with respect to α
Procedure:
(1) scan database TD, generate its full set of isomorphic trees, ITD
(2) scan database ITD, count the number of occurrences for each tree t
(3) calculate the support of each tree
(4) select the trees whose supports are larger than α and detect isomorphic trees; if m trees are
isomorphic, select one of them and discard the others
(5) output the frequent trees
Algorithm 2. fistm (TD; α) (Frequent interaction subtree pattern mining)
Input: a tree database TD and a support threshold α
Output: all frequent subtree patterns with respect to α
Procedure:
(1) i= 0
(2) scan database TD, calculate the support of each node
(3) select the nodes whose supports are larger than α to
form F1
(4) i =i + 1
(5) for each tree ti
in Fi
, do
(6) for each node t1
in F1
, do
(7) join ti
and t1
to generate Ci+1
(8) Subtree Support Calculating (TD; ti+1
)
//calculate the support of each tree in Ci+1
(9) if there are any trees whose supports are larger than α, then select them to form Fiþ1 and
return to Step (4)
(10) else output the frequent subtrees whose supports are Larger than α
Pro
(E)
Pro
(L)
Pos
(B)
6. International Journal of Computer-Aided technologies (IJCAx) Vol.1,No.2/3,October 2014
22
Subprocedure. Subtree Support Calculating (TD, st)
(1) count=0
(2) supp(st)= 0
(3) for each tree t € TD do
(4) create subtrees S of t with any item s € S, |s| = |st|
(5) flag false
(6) for each item s €S do
(7) generate isomorphic trees IS of s
(8) for each item is € IS do
(9) if tsc(is)= tsc(st) then
(10) count =count + 1
(11) flag = true
(12) break
(13) if flag = true then
(14) break
(15) supp(st)= count/|TD|
(16) return supp(st)
Table 1 .Notation
Notation Description
TD A dataset of interaction trees
ITD The full set of isomorphic trees to TD
T A tree
tk
A subtree with k nodes i.e k-subtree
Ck
A set of candidates with k nodes
Fk
A set of frequent k- subtrees
Α A support threshold minsup
The support of T is defined as
)ܶ(ݑݏ =
݊ܶ ݂ ݏ݁ܿ݊݁ݎ݅ܿܿ ݂ ݎܾ݁݉ݑ
ܦܶ ݊݅ ݏ݁݁ݎݐ ݂ ݎܾ݁݉ݑ݊ ݈ܽݐݐ
:
4.Applications
1. Corporate Meetings; - Meeting is integral part of every organization To analyze the
meeting output is of great concerned for organization. So this system can help the
company to predict the meeting output.
2. Business Analyst:- Business Analyst is always concerned for participant behavior in
meeting. The participant behavior means who talks most time or who talks for very less
time, who talks positively or negatively in meetings.
3. Civil Court:- This system is used for Lawyers to analyze the case study and accordingly
study the different cases.
7. International Journal of Computer-Aided technologies (IJCAx) Vol.1,No.2/3,October 2014
23
4. Statistics Evaluation of Viewers for Reality Show:- Viewers give their views for the
show online for eg on facebook , tweeter so these views can be categories and result of
viewers can be evaluate.
5.Conclusion
In this report, human interaction system is proposed which extract the contents of meeting and
predicts the output of meeting. A tree based mining approach is used for discovering frequent
patterns of human interaction in meetings discussion. For filtering the meeting contents stop
words removal and steaming is applied. To classify the conversation simple classification
technique is used. Frequent pattern mining algorithm is used to extract the frequent tree and
meeting output is generated. Proposed system also predicts behavior of meeting and determined
the behavior of participants. It determines the persons who proposed a lot of ideas, the persons
who were critical, whether all members agreed on the outcome, who did not give his opinion,
who spoke a little or a lot.
ACKNOWLEDGEMENTS
It is my pleasure to get this opportunity to thank my beloved and respected Guide Prof.
K.S.Korabu who imparted his valuable knowledge specifically related to image processing. We
are grateful to department of Information Technology SCOE, Pune for providing us infrastructure
facilities and moral support.
REFERENCES
[1] G. Casas-Garriga, “Discovering Unbounded Episodes in Sequential Data,” Proc. European Conf.
Principles and Practice of Knowledge Discovery in Databases (PKDD ’03), pp. 83-94, 2003.
[2] T. Morita, Y. Hirano, Y. Sumi, S. Kajita, and K. Mase, “A Pattern Mining Method for Interpretation of
Interaction,” Proc. Int’l Conf.Multimodal Interfaces (ICMI ’05), pp. 267-273, 2005.
[3] D. Gatica-Perez, I. McCowan, D. Zhang, and S. Bengio, “Detecting Group Interest-Level in
Meetings,” Proc. IEEE Int’l Conf. Acoustic, Speech, and Signal Processing, vol. 1, pp. 489-492, 2005.
[4] Zhiwen Yu; Zhiyong Yu; Aoyama, H.; Ozeki, M.; Nakamura, Y., "Capture, recognition, and
visualization of human semantic interactions in meetings," Pervasive Computing and Communications
(PerCom), 2010 IEEE International Conference on , vol., no., pp.107,115, March 29 2010-April 2
2010.
[5] Z.W. Yu, Z.Y. Yu, Y. Ko, X. Zhou, and Y. Nakamura, “Inferring Human Interactions in Meetings: A
Multimodal Approach,” Proc. Sixth Int’l Conf. Ubiquitous Intelligence and Computing (UIC ’09),pp.
14-24, July 2009.
[6] Z.W. Yu, Z.Y. Yu, Y. Ko, X. Zhou, and Y. Nakamura, “Tree-based mining for discovering patterns of
human interaction in meetings,” Proc.IEEE Transactions on knowledge and data engineering, vol. 24,
no. 4, april 2012.
[7] Garg, N. P., Favre, S., Salamin, H., Tur, D. H., and Vinciarelli, A Role Recognition for Meeting
Participants: an Approach Based on Lexical Information and Social Network Analysis. In Proc. ACM
Multimedia 2008, 693-696.
[8] Chih-Wei Hsu, Chih-Chung Chang, and Chih-Jen Lin,”A Practical Guide to Support Vector
Classification”
[9] Chang, C.C., Lin, C.J.: LIBSVM: a library for support vector machines (2001),
http://www.csie.ntu.edu.tw/~cjlin/libsvm
8. International Journal of Computer-Aided technologies (IJCAx) Vol.1,No.2/3,October 2014
24
[10]Weka (2008), http://www.cs.waikato.ac.nz/ml/weka/ .
[11]Minqing Hu and Bing Liu."Mining and Summarizing Customer Reviews."Proceedings of the ACM
SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2004), Aug 22-
25, 2004, Seattle,Washington, USA,
Author
Prashant P Puri He is student at Sinhgad College of Engineering, Pune. He received his
bachelor degree in Information Technology in 2011, and currently pursuing M.E. His
current research interest includes developing mining methods for inferring human
interactions in meetings in the domain of Data Mining.
Kirti Korabu She received her bachelor degree and Master Degree in Computer science.
She has a experience of 18.5 yrs and currently working as Associate Professor in Sinhgad
College of Engineering. She has published five international journal papers. Her current
research interest includes Data Mining, Information Retrieval, Software Engineering,
Database Management Systems, Data Structures and Algorithms, Theory of computation.
She is member of LMISTE, LMCSI.