Data Mining for Social Network Data (Annals of Information Systems)

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9781441962867: Data Mining for Social Network Data (Annals of Information Systems)

Driven by counter-terrorism efforts, marketing analysis and an explosion in online social networking in recent years, data mining has moved to the forefront of information science. This proposed Special Issue on Data Mining for Social Network Data will present a broad range of recent studies in social networking analysis. It will focus on emerging trends and needs in discovery and analysis of communities, solitary and social activities, activities in open for a and commercial sites as well. It will also look at network modeling, infrastructure construction, dynamic growth and evolution pattern discovery using machine learning approaches and multi-agent based simulations. Editors are three rising stars in world of data mining, knowledge discovery, social network analysis, and information infrastructures, and are anchored by Springer author/editor Hsinchun Chen (Terrorism Informatics; Medical Informatics; Digital Government), who is one of the most prominent intelligence analysis and data mining experts in the world.

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Social Network Data Mining: Research Questions, Techniques, and Applications Nasrullah Memon, Jennifer Xu, David L. Hicks and Hsinchun Chen Automatic expansion of a social network using sentiment analysis Hristo Tanev, Bruno Pouliquen, Vanni Zavarella and Ralf Steinberger Automatic mapping of social networks of actors from text corpora: Time series analysis James A. Danowski and Noah Cepela A social network based recommender system (SNRS) Jianming He and Wesley W. Chu Network analysis of U.S. air transportation network Guangying Hua, Yingjie Sun, and Dominique Haughton Identifying high-status nodes in knowledge networks Siddharth Kaza and Hsinchun Chen Modularity for bipartite networks Tsuyoshi Murata ONDOCS: Ordering nodes to detect overlapping community structure Jiyang Chen, Osmar R. Zaiane, J¨org Sander, and Randy Goebel Framework for Fast Identification of Community Structures in Large-Scale Social Networks Yutaka I. Leon-Suematsu and Kikuo Yuta Geographically organized small communities and the hardness of clustering social networks Miklós Kurucz and András A. Benczúr Integrating genetic algorithms and fuzzy logic for web structure optimization Iltae Lee, Negar Koochakzadeh, Keivan Kianmehr, Reda Alhajj, and Jon Rokne

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Book Description Springer. Paperback. Book Condition: New. This item is printed on demand. Paperback. 226 pages. Driven by counter-terrorism efforts, marketing analysis and an explosion in online social networking in recent years, data mining has moved to the forefront of information science. This proposed Special Issue on Data Mining for Social Network Data will present a broad range of recent studies in social networking analysis. It will focus on emerging trends and needs in discovery and analysis of communities, solitary and social activities, activities in open for a and commercial sites as well. It will also look at network modeling, infrastructure construction, dynamic growth and evolution pattern discovery using machine learning approaches and multi-agent based simulations. Editors are three rising stars in world of data mining, knowledge discovery, social network analysis, and information infrastructures, and are anchored by Springer authoreditor Hsinchun Chen (Terrorism Informatics; Medical Informatics; Digital Government), who is one of the most prominent intelligence analysis and data mining experts in the world. This item ships from La Vergne,TN. Paperback. Bookseller Inventory # 9781441962867

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