05119nam 22008055 450 99646620450331620230221232234.03-642-14929-410.1007/978-3-642-14929-0(CKB)2670000000036366(SSID)ssj0000446263(PQKBManifestationID)11262647(PQKBTitleCode)TC0000446263(PQKBWorkID)10491746(PQKB)10142785(DE-He213)978-3-642-14929-0(MiAaPQ)EBC3065627(PPN)149017987(EXLCZ)99267000000003636620100808d2010 u| 0engurnn#008mamaatxtccrAdvances in Social Network Mining and Analysis[electronic resource] Second International Workshop, SNAKDD 2008, Las Vegas, NV, USA, August 24-27, 2008. Revised Selected Papers /edited by C. Lee Giles, Marc Smith, John Yen, Haizheng Zhang1st ed. 2010.Berlin, Heidelberg :Springer Berlin Heidelberg :Imprint: Springer,2010.1 online resource (XI, 131 p. 47 illus.)Theoretical Computer Science and General Issues,2512-2029 ;5498" ... co-locates with the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD)"--Pref.3-642-14928-6 Includes bibliographical references and index.Leveraging Label-Independent Features for Classification in Sparsely Labeled Networks: An Empirical Study -- Community Detection Using a Measure of Global Influence -- Communication Dynamics of Blog Networks -- Finding Spread Blockers in Dynamic Networks -- Social Network Mining with Nonparametric Relational Models -- Using Friendship Ties and Family Circles for Link Prediction -- Information Theoretic Criteria for Community Detection.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.Theoretical Computer Science and General Issues,2512-2029 ;5498Application softwareArtificial intelligenceDatabase managementInformation storage and retrieval systemsData miningComputer networksComputer and Information Systems ApplicationsArtificial IntelligenceDatabase ManagementInformation Storage and RetrievalData Mining and Knowledge DiscoveryComputer Communication NetworksApplication software.Artificial intelligence.Database management.Information storage and retrieval systems.Data mining.Computer networks.Computer and Information Systems Applications.Artificial Intelligence.Database Management.Information Storage and Retrieval.Data Mining and Knowledge Discovery.Computer Communication Networks.005.7Giles C. Leeedthttp://id.loc.gov/vocabulary/relators/edtSmith Marcedthttp://id.loc.gov/vocabulary/relators/edtYen Johnedthttp://id.loc.gov/vocabulary/relators/edtZhang Haizhengedthttp://id.loc.gov/vocabulary/relators/edtInternational Conference on Knowledge Discovery & Data Mining(14th :2008 :Las Vegas, Nev.)BOOK996466204503316Advances in Social Network Mining and Analysis2830672UNISA