The Encyclopedia of Social Network Analysis and Mining (ESNAM) is the first major reference work to integrate fundamental concepts and research directions in the areas of social networks and applications to data mining. The second edition of ESNAM is a truly outstanding reference appealing to researchers, practitioners, instructors and students (both undergraduate and graduate), as well as the general public. This updated reference integrates all basics concepts and research efforts under one umbrella. Coverage has been expanded to include new emerging topics such as crowdsourcing, opinion…mehr
The Encyclopedia of Social Network Analysis and Mining (ESNAM) is the first major reference work to integrate fundamental concepts and research directions in the areas of social networks and applications to data mining. The second edition of ESNAM is a truly outstanding reference appealing to researchers, practitioners, instructors and students (both undergraduate and graduate), as well as the general public. This updated reference integrates all basics concepts and research efforts under one umbrella. Coverage has been expanded to include new emerging topics such as crowdsourcing, opinion mining, and sentiment analysis. Revised content of existing material keeps the encyclopedia current. The second edition is intended for college students as well as public and academic libraries. It is anticipated to continue to stimulate more awareness of social network applications and research efforts. The advent of electronic communication, and in particular on-line communities, have created social networks of hitherto unimaginable sizes. Reflecting the interdisciplinary nature of this unique field, the essential contributions of diverse disciplines, from computer science, mathematics, and statistics to sociology and behavioral science, are described among the 300 authoritative yet highly readable entries. Students will find a world of information and insight behind the familiar façade of the social networks in which they participate. Researchers and practitioners will benefit from a comprehensive perspective on the methodologies for analysis of constructed networks, and the data mining and machine learning techniques that have proved attractive for sophisticated knowledge discovery in complex applications. Also addressed is the application of social network methodologies to other domains, such as web networks and biological networks.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Reda Alhajj is a Professor in the Department of Computer Science at the University of Calgary. He published over 350 papers in reputable journals and fully refereed international conferences. He served as program chair of several conferences and on the program committee of large number of International conferences including IEEE ICDE, IEEE ICDM, IEEE IAT, IEEE WI, SIAM DM, AAAI, IJCAI, etc. He also served as guest editor of several special issues and is currently the program chair of IEEE IRI 2011, CaSoN 2011, ASONAM 2011, IEEE HPPC 2011 and OSINT-WM 2011. He is on the editorial board of several journals; he associate editor of IEEE SMC- Part C. He is editor in chief of SNAM Journal and the Lecture Notes in Social Networks series by Springer. He frequently gives invited talks in North America, Europe and the Middle East. Dr. Alhajj's has a large research group which in 2010 had 10 PhD and 8 MSc students working primarily in the areas of biocomputing and biodata analysis, datamining, multiagent systems, schema integration and re-engineering, social networks and XML. He received Outstanding Achievements in Supervision Award from the Faculty of Graduate Studies at the University of Calgary. He closely collaborates with RBC Canada. He is married and has three daughters and two sons. Jon Rokne is a Professor in the Department of Computer Science at the University of Calgary where he chaired the department from 1989 to 1996. He obtained an M. Sc. from the University of Alberta and a Ph. D. from the University of Calgary, both in the area of applied mathematics with a numerical analysis emphasis. His main applied mathematics interests have been interval analysis and global optimization and he has co-authored three books in these areas. In computer science the focus has been computer graphics and physically and biologically based computer simulations with publications on the visual simulation of leaves, auroras, sky, Chinese calligraphy, seismic visualization and ball lightening. He has published one jointly authored computer science book entitled "Light Interaction with Plants". He has also published papers in the areas of computational geometry, computer-aided design and social networks. In 2009 and 2010 he was the publicity chair for ASONAM. His extracurricular activities have included skiing, hiking and mountaineering. He is married and his wife teaches in the Faculty of Education of the University of Calgary. He has two sons.
Inhaltsangabe
Applied Computational Geometry for Social Networks. Basics of Social Network Model Construction and Evolution. Crowdsourcing, Opinion Mining, Fusion and Influence Analysis. Current and Future Research Directions. Data Collection, Data Extraction, and Data Preparation for Social Networks Analysis and Mining. Data Management for Social Networks and Social Media. Data Mining and Machine Learning Techniques for Social Networks. Graph Theory for Social Networks (Sociograms). History of Social Networks: Past, Present and Future. Internet, Web 2.0, Web Services and Semantic Web. Linear Algebra and Statistics for Social Networks. Online Social Networks, Social Networking Sites and Social Media. Privacy and Security Issues in Social Networks. Sentiment Analysis and Recommender Systems. Social Communities. Social Network Analysis. Social Network Applications in Business, Organizations, Industry and Case studies. Social Network Applications in Homeland Security, Terrorism, Fraud Detection, Public Sector, Politics and Case studies. Social Network Applications in Scientific, Engineering, Medical Domain and Case studies. Social Network Construction, Visualization and Analysis Tools. Spatio Temporal Aspects in Social Networks and Social Media. Static Versus Dynamic Networks. Technology for Online Social Networking and Human Computer Interaction.
Applied Computational Geometry for Social Networks. Basics of Social Network Model Construction and Evolution. Crowdsourcing, Opinion Mining, Fusion and Influence Analysis. Current and Future Research Directions. Data Collection, Data Extraction, and Data Preparation for Social Networks Analysis and Mining. Data Management for Social Networks and Social Media. Data Mining and Machine Learning Techniques for Social Networks. Graph Theory for Social Networks (Sociograms). History of Social Networks: Past, Present and Future. Internet, Web 2.0, Web Services and Semantic Web. Linear Algebra and Statistics for Social Networks. Online Social Networks, Social Networking Sites and Social Media. Privacy and Security Issues in Social Networks. Sentiment Analysis and Recommender Systems. Social Communities. Social Network Analysis. Social Network Applications in Business, Organizations, Industry and Case studies. Social Network Applications in Homeland Security, Terrorism, Fraud Detection, Public Sector, Politics and Case studies. Social Network Applications in Scientific, Engineering, Medical Domain and Case studies. Social Network Construction, Visualization and Analysis Tools. Spatio Temporal Aspects in Social Networks and Social Media. Static Versus Dynamic Networks. Technology for Online Social Networking and Human Computer Interaction.
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