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Link Mining: Models, Algorithms, and Applications. 2010 ed.
・ISBN 978-1-4939-0147-0 paper EUR 199.99
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| 著者・編者 | Yu, Philip S. / Han, Jiawei / Faloutsos, Christos (eds.), |
|---|---|
| 出版社 | (Springer-Verlag New York Inc., US) |
| 出版年月 | 2014 |
| ページ数 | 586 pp. |
| 言語 | ENG |
| ニュース番号 | <A05-51880> |
解説
With the recent ?ourishing research activities on Web search and mining, social networkanalysis,informationnetworkanalysis,informationretrieval,linkana- sis,andstructuraldatamining,researchonlinkmininghasbeenrapidlygrowing, forminganew?eldofdatamining. Traditionaldataminingfocuseson"?at"or"isolated"datainwhicheachdata objectisrepresentedasanindependentattributevector. However,manyreal-world data sets are inter-connected, much richer in structure, involving objects of h- erogeneoustypesandcomplexlinks. Hence,thestudyoflinkminingwillhavea highimpactonvariousimportantapplicationssuchasWebandtextmining,social networkanalysis,collaborative?ltering,andbioinformatics. Asanemergingresearch?eld,therearecurrentlynobooksfocusingonthetheory andtechniquesaswellastherelatedapplicationsforlinkmining,especiallyfrom aninterdisciplinarypointofview. Ontheotherhand,duetothehighpopularity oflinkagedata,extensiveapplicationsrangingfromgovernmentalorganizationsto commercial businesses to people's daily life call for exploring the techniques of mininglinkagedata. Therefore,researchersandpractitionersneedacomprehensive booktosystematicallystudy,furtherdevelop,andapplythelinkminingtechniques totheseapplications. Thisbookcontainscontributedchaptersfromavarietyofprominentresearchers inthe?eld. Whilethechaptersarewrittenbydifferentresearchers,thetopicsand contentareorganizedinsuchawayastopresentthemostimportantmodels,al- rithms,andapplicationsonlinkmininginastructuredandconciseway. Giventhe lackofstructurallyorganizedinformationonthetopicoflinkmining,thebookwill provideinsightswhicharenoteasilyaccessibleotherwise. Wehopethatthebook willprovideausefulreferencetonotonlyresearchers,professors,andadvanced levelstudentsincomputersciencebutalsopractitionersinindustry. Wewouldliketoconveyourappreciationtoallauthorsfortheirvaluablec- tributions. WewouldalsoliketoacknowledgethatthisworkissupportedbyNSF throughgrantsIIS-0905215,IIS-0914934,andDBI-0960443. Chicago,Illinois PhilipS. Yu Urbana-Champaign,Illinois JiaweiHan Pittsburgh,Pennsylvania ChristosFaloutsos v Contents Part I Link-Based Clustering 1 Machine Learning Approaches to Link-Based Clustering...3 Zhongfei(Mark)Zhang,BoLong,ZhenGuo,TianbingXu, andPhilipS. Yu 2 Scalable Link-Based Similarity Computation and Clustering...45 XiaoxinYin,JiaweiHan,andPhilipS. Yu 3 Community Evolution and Change Point Detection in Time-Evolving Graphs...73 JimengSun,SpirosPapadimitriou,PhilipS. Yu,andChristosFaloutsos Part II Graph Mining and Community Analysis 4 A Survey of Link Mining Tasks for Analyzing Noisy and Incomplete Networks...107 GalileoMarkNamata,HossamSharara,andLiseGetoor 5 Markov Logic: A Language and Algorithms for Link Mining...135 PedroDomingos,DanielLowd,StanleyKok,AniruddhNath,Hoifung Poon,MatthewRichardson,andParagSingla 6 Understanding Group Structures and Properties in Social Media...163 LeiTangandHuanLiu 7 Time Sensitive Ranking with Application to Publication Search...187 XinLi,BingLiu,andPhilipS. Yu 8 Proximity Tracking on Dynamic Bipartite Graphs: Problem De?nitions and Fast Solutions...211 Hanghang Tong, Spiros Papadimitriou, Philip S. Yu, andChristosFaloutsos vii viii Contents 9 Discriminative Frequent Pattern-Based Graph Classi?cation...237 HongCheng,XifengYan,andJiaweiHan Part III Link Analysis for Data Cleaning and Information Integration 10 Information Integration for Graph Databases...2 65 Ee-PengLim,AixinSun,AnwitamanDatta,andKuiyuChang 11 Veracity Analysis and Object Distinction...283 XiaoxinYin,JiaweiHan,andPhilipS. Yu Part IV Social Network Analysis 12 Dynamic Community Identi?cation...