Advances in Social Network Mining and Analysis: Second International Workshop, Snakdd 2008 Las Vegas, Nv, USA, August 24-27, 2008

Giles, C. Lee (Editor)

ISBN 10: 3642149286 / ISBN 13: 9783642149283

Published by Springer-Verlag New York Inc, 2010

About this Item

142 pages. 9.00x6.00x0.25 inches. In Stock.

Seller Inventory # x-3642149286

Bibliographic Details

• Title: Advances in Social Network Mining and Analysis: Second International Workshop, Snakdd 2008 Las Vegas, Nv, USA, August 24-27, 2008
• Publisher: Springer-Verlag New York Inc
• Publication Date: 2010
• Language: English
• ISBN 10: 3642149286
• ISBN 13: 9783642149283
• Binding: Paperback
• Condition: Brand New
• Weight: 0.23 kilograms

About this title

Synopsis

This year’s volume of Advances in Social Network Analysis contains the p- ceedings for the Second International Workshop on Social Network Analysis (SNAKDD 2008). The annual workshop co-locates with the ACM SIGKDD - ternational Conference on Knowledge Discovery and Data Mining (KDD). The second SNAKDD workshop was held with KDD 2008 and received more than 32 submissions on social network mining and analysis topics. We accepted 11 regular papers and 8 short papers. Seven of the papers are included in this volume. In recent years, social network research has advanced signi?cantly, thanks to the prevalence of the online social websites and instant messaging systems as well as the availability of a variety of large-scale o?ine social network systems. These social network systems are usually characterized by the complex network structures and rich accompanying contextual information. Researchers are - creasingly interested in addressing a wide range of challenges residing in these disparate social network systems, including identifying common static topol- ical properties and dynamic properties during the formation and evolution of these social networks, and how contextual information can help in analyzing the pertaining socialnetworks.These issues haveimportant implications oncom- nitydiscovery,anomalydetection,trendpredictionandcanenhanceapplications in multiple domains such as information retrieval, recommendation systems, - curity and so on.