Pub Date : 2017-10-01DOI: 10.1109/BESC.2017.8256408
Lukasz Oliwa, J. Kozlak
Finding the most relevant facts and the relations between each of them is not a trivial task due to vast amount of information in the Internet. Different significant events influence the World Wide Web and the blogosphere and because of its size and variety we are often not aware that such events take or took place. The identification of significant changes of the blogosphere may inform us about their occurrences. We define a state of social portal taking into consideration general network features, measures of key elements and distribution of these measures, neighbourhood distributions of nodes and existing communities, and analyse the changes of these factors in the subsequent network states to identify anomalies, possibly caused by significant events. Two portals (Polish Salon24 blog portal and Huffington Post) are used as cases in the evaluation part.
{"title":"Anomaly detection in dynamic social networks for identifying key events","authors":"Lukasz Oliwa, J. Kozlak","doi":"10.1109/BESC.2017.8256408","DOIUrl":"https://doi.org/10.1109/BESC.2017.8256408","url":null,"abstract":"Finding the most relevant facts and the relations between each of them is not a trivial task due to vast amount of information in the Internet. Different significant events influence the World Wide Web and the blogosphere and because of its size and variety we are often not aware that such events take or took place. The identification of significant changes of the blogosphere may inform us about their occurrences. We define a state of social portal taking into consideration general network features, measures of key elements and distribution of these measures, neighbourhood distributions of nodes and existing communities, and analyse the changes of these factors in the subsequent network states to identify anomalies, possibly caused by significant events. Two portals (Polish Salon24 blog portal and Huffington Post) are used as cases in the evaluation part.","PeriodicalId":142098,"journal":{"name":"2017 International Conference on Behavioral, Economic, Socio-cultural Computing (BESC)","volume":"110 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122977437","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-10-01DOI: 10.1109/BESC.2017.8357663
Pan Liao, Yuan Sun, Shiwei Ye, Xin Li, Guiping Su, Yi Sun
As massive open online courses (MOOCs) and online intelligent tutoring systems(ITS) have become increasingly widespread, the number of learners enrolled in online courses has shown explosive growth. However, these learners are likely to have acquired knowledge from diverse educational and vocational backgrounds. Therefore, it is unwise to apply the same criteria and assessment questions to assess all learners' abilities without differentiation. Therefore, the demand for the adaptive arrangement of questions for online learners is ever critical. Deep learning is a new increasingly popular approach for handling extraordinarily complex problems such as image recognition and natural language processing. In this research, we use neural networks to forecast learners' multi-question performance on new test questions and propose a new concept called predictable property for the first time to explain the reasons why neural networks can be applied to predict learners' multi-question performance based on their previous question responses. This approach means that fewer questions need to be answered by learners although more information can be gathered about them through the use of deep-learning-based techniques. Finally, we use both artificial datasets generated by cognitive models and three real-world datasets to validate the algorithm's performance. Experiments show a promising research result when using deep learning to predict learner performance in multi-question tasks and can ultimately provide more accurate adaptive tests for learners.
{"title":"Predicting learners' multi-question performance based on neural networks","authors":"Pan Liao, Yuan Sun, Shiwei Ye, Xin Li, Guiping Su, Yi Sun","doi":"10.1109/BESC.2017.8357663","DOIUrl":"https://doi.org/10.1109/BESC.2017.8357663","url":null,"abstract":"As massive open online courses (MOOCs) and online intelligent tutoring systems(ITS) have become increasingly widespread, the number of learners enrolled in online courses has shown explosive growth. However, these learners are likely to have acquired knowledge from diverse educational and vocational backgrounds. Therefore, it is unwise to apply the same criteria and assessment questions to assess all learners' abilities without differentiation. Therefore, the demand for the adaptive arrangement of questions for online learners is ever critical. Deep learning is a new increasingly popular approach for handling extraordinarily complex problems such as image recognition and natural language processing. In this research, we use neural networks to forecast learners' multi-question performance on new test questions and propose a new concept called predictable property for the first time to explain the reasons why neural networks can be applied to predict learners' multi-question performance based on their previous question responses. This approach means that fewer questions need to be answered by learners although more information can be gathered about them through the use of deep-learning-based techniques. Finally, we use both artificial datasets generated by cognitive models and three real-world datasets to validate the algorithm's performance. Experiments show a promising research result when using deep learning to predict learner performance in multi-question tasks and can ultimately provide more accurate adaptive tests for learners.","PeriodicalId":142098,"journal":{"name":"2017 International Conference on Behavioral, Economic, Socio-cultural Computing (BESC)","volume":"91 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123163348","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-10-01DOI: 10.1109/BESC.2017.8256370
A. Opaliński, P. Nastalek, B. Mrzygłód, N. Celejewska-Wójcik, M. Glowacki, G. Bochenek, K. Regulski, K. Sładek, A. Kania
The paper presents the system for the integration of heterogeneous data sources in the domain of Obstructive Sleep Apnea. The main goal of the system is to facilitate patient diagnose and treatment process by integration of the results of performed medical examinations and analyzes. Data source contains: clinical interviews, physical examinations, lab tests, and the data collected from the devices used to monitor patient's sleep parameters (PSG, CPAP). This article describes the concept of the system, its main functionalities, IT architecture and technology and some details of its implementation. Also the data sources and the methods of data acquisition from medical devices integrated with the system are characterized. In addition, basic methods of analyzing data gathered in the system are presented, which in the future can be developed towards automatic mechanisms supporting the process of diagnosis and treatment of patients in this domain.
{"title":"The system for integration of heterogeneous data sources in the domain of Obstructive Sleep Apnea","authors":"A. Opaliński, P. Nastalek, B. Mrzygłód, N. Celejewska-Wójcik, M. Glowacki, G. Bochenek, K. Regulski, K. Sładek, A. Kania","doi":"10.1109/BESC.2017.8256370","DOIUrl":"https://doi.org/10.1109/BESC.2017.8256370","url":null,"abstract":"The paper presents the system for the integration of heterogeneous data sources in the domain of Obstructive Sleep Apnea. The main goal of the system is to facilitate patient diagnose and treatment process by integration of the results of performed medical examinations and analyzes. Data source contains: clinical interviews, physical examinations, lab tests, and the data collected from the devices used to monitor patient's sleep parameters (PSG, CPAP). This article describes the concept of the system, its main functionalities, IT architecture and technology and some details of its implementation. Also the data sources and the methods of data acquisition from medical devices integrated with the system are characterized. In addition, basic methods of analyzing data gathered in the system are presented, which in the future can be developed towards automatic mechanisms supporting the process of diagnosis and treatment of patients in this domain.","PeriodicalId":142098,"journal":{"name":"2017 International Conference on Behavioral, Economic, Socio-cultural Computing (BESC)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117298514","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-10-01DOI: 10.1109/BESC.2017.8256411
S. Rudnicki
The question of the social impact of science has become a crucial issue in the current debates on the role of science in society and, importantly, one of the criteria upon which academic institutions and scholars are assessed. However, in both the public debate and evaluation procedures there is a limited understanding of the nature of the social impact of science. The aim of this paper it to deconstruct the predominant views as based upon the simplistic model of knowledge transfer, show its theoretical shortcomings, and contrast it with the proposed model of translation, derived from actor-network theory.
{"title":"Transfer or translation? The actor-network theory approach to the social impact of science","authors":"S. Rudnicki","doi":"10.1109/BESC.2017.8256411","DOIUrl":"https://doi.org/10.1109/BESC.2017.8256411","url":null,"abstract":"The question of the social impact of science has become a crucial issue in the current debates on the role of science in society and, importantly, one of the criteria upon which academic institutions and scholars are assessed. However, in both the public debate and evaluation procedures there is a limited understanding of the nature of the social impact of science. The aim of this paper it to deconstruct the predominant views as based upon the simplistic model of knowledge transfer, show its theoretical shortcomings, and contrast it with the proposed model of translation, derived from actor-network theory.","PeriodicalId":142098,"journal":{"name":"2017 International Conference on Behavioral, Economic, Socio-cultural Computing (BESC)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126350457","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-10-01DOI: 10.1109/BESC.2017.8256397
Uma-E.-Hani, S. Naz, I. Hameed
Brain is the central organ of the human body which controls nervous system. In this paper, we give a brief insight of different techniques and contribution of different people for segmentation and detection of brain tumor. Different methodologies are proposed by different researchers. The MRI scan image considers as a high quality input for experiments as compared to other scans. In the future, we will develop a deep learning based automated brain tumor detection system and will compare with the existing state of the art techniques for better and more accurate results.
{"title":"Automated techniques for brain tumor segmentation and detection: A review study","authors":"Uma-E.-Hani, S. Naz, I. Hameed","doi":"10.1109/BESC.2017.8256397","DOIUrl":"https://doi.org/10.1109/BESC.2017.8256397","url":null,"abstract":"Brain is the central organ of the human body which controls nervous system. In this paper, we give a brief insight of different techniques and contribution of different people for segmentation and detection of brain tumor. Different methodologies are proposed by different researchers. The MRI scan image considers as a high quality input for experiments as compared to other scans. In the future, we will develop a deep learning based automated brain tumor detection system and will compare with the existing state of the art techniques for better and more accurate results.","PeriodicalId":142098,"journal":{"name":"2017 International Conference on Behavioral, Economic, Socio-cultural Computing (BESC)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122705211","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-10-01DOI: 10.1109/BESC.2017.8256387
A. Wróbel, Konrad Komnata, Krzysztof Rudek
This paper covers aspects of governing information data on enterprise level using IBM solutions. In particular it focus on one of the key elements of governance — data lineage for EU GDPR regulations.
{"title":"IBM data governance solutions","authors":"A. Wróbel, Konrad Komnata, Krzysztof Rudek","doi":"10.1109/BESC.2017.8256387","DOIUrl":"https://doi.org/10.1109/BESC.2017.8256387","url":null,"abstract":"This paper covers aspects of governing information data on enterprise level using IBM solutions. In particular it focus on one of the key elements of governance — data lineage for EU GDPR regulations.","PeriodicalId":142098,"journal":{"name":"2017 International Conference on Behavioral, Economic, Socio-cultural Computing (BESC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114095748","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-10-01DOI: 10.1109/BESC.2017.8256403
I. Ting, Wun Sheng Liou, Dario Liberona, Shyue-Liang Wang, G. T. Bermúdez
In recent years, users are widely intend to express and share their opinions over the Internet. However, due to the characters of social media, it appears negative use of social media. Cyberbullying is one of the abuse behavior in the Internet as well as a very serious social problem. Under this background and motivation, it can help to prevent the happen of cyberbullying if we can develop relevant techniques to discover cyberbullying in social media. Thus, in this paper we propose an approach based on social networks analysis and data mining for cyberbullying detection. In the approach, there are three main techniques for cyberbullying discovery will be studied, including keyword matching technique, opinion mining and social network analysis. In addition to the approach, we will also discuss the experimental design for the evaluation of the performance.
{"title":"Towards the detection of cyberbullying based on social network mining techniques","authors":"I. Ting, Wun Sheng Liou, Dario Liberona, Shyue-Liang Wang, G. T. Bermúdez","doi":"10.1109/BESC.2017.8256403","DOIUrl":"https://doi.org/10.1109/BESC.2017.8256403","url":null,"abstract":"In recent years, users are widely intend to express and share their opinions over the Internet. However, due to the characters of social media, it appears negative use of social media. Cyberbullying is one of the abuse behavior in the Internet as well as a very serious social problem. Under this background and motivation, it can help to prevent the happen of cyberbullying if we can develop relevant techniques to discover cyberbullying in social media. Thus, in this paper we propose an approach based on social networks analysis and data mining for cyberbullying detection. In the approach, there are three main techniques for cyberbullying discovery will be studied, including keyword matching technique, opinion mining and social network analysis. In addition to the approach, we will also discuss the experimental design for the evaluation of the performance.","PeriodicalId":142098,"journal":{"name":"2017 International Conference on Behavioral, Economic, Socio-cultural Computing (BESC)","volume":"314 5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132648795","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-10-01DOI: 10.1109/BESC.2017.8256391
Xinda Wang, Xuri Tang, Weiguang Qu, Min Gu
This paper proposes an algorithm for unsupervised Word Sense Disambiguation to bypass the knowledge bottleneck faced by supervised approaches. By simulating the semantic inference process performed by human language users, the algorithm makes use of a thesaurus to obtain potential substitute words for the target word in a sentence, builds substitute constructs by replacing the target word with substitute words, uses large-scale dependency parsed corpora to calculate the likelihood of the substitute constructs, and then obtain the best substitute word which help specify the sense of the target word in the sentence. Experiments with WordNet 2.1 and the corpora English Gigawords on the lexical sample task in SemEval-2007 show that the algorithm achieves the-state-of-art accuracy for both nouns and verbs, which are 3–5 percent higher than the best unsupervised system in SemEval-2007, given the condition that the knowledge source provides sufficient information.
{"title":"Word sense disambiguation by semantic inference","authors":"Xinda Wang, Xuri Tang, Weiguang Qu, Min Gu","doi":"10.1109/BESC.2017.8256391","DOIUrl":"https://doi.org/10.1109/BESC.2017.8256391","url":null,"abstract":"This paper proposes an algorithm for unsupervised Word Sense Disambiguation to bypass the knowledge bottleneck faced by supervised approaches. By simulating the semantic inference process performed by human language users, the algorithm makes use of a thesaurus to obtain potential substitute words for the target word in a sentence, builds substitute constructs by replacing the target word with substitute words, uses large-scale dependency parsed corpora to calculate the likelihood of the substitute constructs, and then obtain the best substitute word which help specify the sense of the target word in the sentence. Experiments with WordNet 2.1 and the corpora English Gigawords on the lexical sample task in SemEval-2007 show that the algorithm achieves the-state-of-art accuracy for both nouns and verbs, which are 3–5 percent higher than the best unsupervised system in SemEval-2007, given the condition that the knowledge source provides sufficient information.","PeriodicalId":142098,"journal":{"name":"2017 International Conference on Behavioral, Economic, Socio-cultural Computing (BESC)","volume":"158 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127414933","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-07-17DOI: 10.1109/BESC.2017.8256364
Sinan S. AlSheikh, K. Shaalan, F. Meziane
Trust can be defined as the vulnerability of trustor towards trustee to meet certain expectations. This paper extends the definition of trust to cover digital world and illustrate the trust model used by most of nowadays online stores. The social media sentiment analysis revealed the sentiments of customers towards traditional Business-to-Consumer (B2C) stores vs modern Consumer-to-Consumer (C2C) market places. Sentiment analysis was performed across multiple industry's like Taxi, hospitality, and online retail industry. The popularity of Negative sentiments was higher towards most of modern C2C market places compared to traditional B2C stores. The popularity of negative posts was linked with the consumers' trust towards the C2C market place offering. However, few C2C companies managed to maintain a high positive posts ration and sometimes they were better than traditional B2C business. Uber and AirBnB surprisingly were not on the top.
{"title":"Consumers' trust and popularity of negative posts in social media: A case study on the integration between B2C and C2C business models","authors":"Sinan S. AlSheikh, K. Shaalan, F. Meziane","doi":"10.1109/BESC.2017.8256364","DOIUrl":"https://doi.org/10.1109/BESC.2017.8256364","url":null,"abstract":"Trust can be defined as the vulnerability of trustor towards trustee to meet certain expectations. This paper extends the definition of trust to cover digital world and illustrate the trust model used by most of nowadays online stores. The social media sentiment analysis revealed the sentiments of customers towards traditional Business-to-Consumer (B2C) stores vs modern Consumer-to-Consumer (C2C) market places. Sentiment analysis was performed across multiple industry's like Taxi, hospitality, and online retail industry. The popularity of Negative sentiments was higher towards most of modern C2C market places compared to traditional B2C stores. The popularity of negative posts was linked with the consumers' trust towards the C2C market place offering. However, few C2C companies managed to maintain a high positive posts ration and sometimes they were better than traditional B2C business. Uber and AirBnB surprisingly were not on the top.","PeriodicalId":142098,"journal":{"name":"2017 International Conference on Behavioral, Economic, Socio-cultural Computing (BESC)","volume":"2016 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128069429","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-07-05DOI: 10.1109/BESC.2017.8256376
Amartya Sanyal, Sanjana Garg, Asim Unmesh
Understanding the evolution of human society, as a complex adaptive system, is a task that has been looked upon from various angles. In this paper, we simulate an agent-based model with a high enough population tractably. To do this, we characterize an entity called society, which helps us reduce the complexity of each step from O(n2) to O(n). We propose a very realistic setting, where we design a joint alternate maximization step algorithm to maximize a certain fitness function, which we believe simulates the way societies develop. Our key contributions include (i) proposing a novel protocol for simulating the evolution of a society with cheap, non-optimal joint alternate maximization steps (ii) providing a framework for carrying out experiments that adhere to this joint-optimization simulation framework (iii) carrying out experiments to show that it makes sense empirically (iv) providing an alternate justification for the use of society in the simulations.
{"title":"Agent based simulation of the evolution of society as an alternate maximzation problem","authors":"Amartya Sanyal, Sanjana Garg, Asim Unmesh","doi":"10.1109/BESC.2017.8256376","DOIUrl":"https://doi.org/10.1109/BESC.2017.8256376","url":null,"abstract":"Understanding the evolution of human society, as a complex adaptive system, is a task that has been looked upon from various angles. In this paper, we simulate an agent-based model with a high enough population tractably. To do this, we characterize an entity called society, which helps us reduce the complexity of each step from O(n2) to O(n). We propose a very realistic setting, where we design a joint alternate maximization step algorithm to maximize a certain fitness function, which we believe simulates the way societies develop. Our key contributions include (i) proposing a novel protocol for simulating the evolution of a society with cheap, non-optimal joint alternate maximization steps (ii) providing a framework for carrying out experiments that adhere to this joint-optimization simulation framework (iii) carrying out experiments to show that it makes sense empirically (iv) providing an alternate justification for the use of society in the simulations.","PeriodicalId":142098,"journal":{"name":"2017 International Conference on Behavioral, Economic, Socio-cultural Computing (BESC)","volume":"195 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130350650","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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