Encyclopedia of Social Network Analysis and Mining,2nd Edition


by 作者: Reda Alhajj,Jon Rokne
Pages: 3431 pages
Publisher Finelybook 出版社: ; 2nd ed. 2018 edition (27 Jun. 2018)
Language 语言: English
ISBN-10 书号: 1493971301
ISBN-13 书号: 9781493971305


About the Author
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 . 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,data
mining,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 visu
alization 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.
Social Network Analysis and Mining Encyclopedia (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.

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