Link Mining

Yu, Philip S. (EDT)/ Han, Jiawei (EDT)/ Faloutsos, Christos (EDT)

Editore: Springer Verlag, 2010
ISBN 10: 1441965149 / ISBN 13: 9781441965141
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Riassunto: 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. . . . . . . . . . . . . . . . . . . . . 265 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. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Contenuti: Link-Based Clustering.- Machine Learning Approaches to Link-Based Clustering.- Scalable Link-Based Similarity Computation and Clustering.- Community Evolution and Change Point Detection in Time-Evolving Graphs.- Graph Mining and Community Analysis.- A Survey of Link Mining Tasks for Analyzing Noisy and Incomplete Networks.- Markov Logic: A Language and Algorithms for Link Mining.- Understanding Group Structures and Properties in Social Media.- Time Sensitive Ranking with Application to Publication Search.- Proximity Tracking on Dynamic Bipartite Graphs: Problem Definitions and Fast Solutions.- Discriminative Frequent Pattern-Based Graph Classification.- Link Analysis for Data Cleaning and Information Integration.- Information Integration for Graph Databases.- Veracity Analysis and Object Distinction.- Social Network Analysis.- Dynamic Community Identification.- Structure and Evolution of Online Social Networks.- Toward Identity Anonymization in Social Networks.- Summarization and OLAP of Information Networks.- Interactive Graph Summarization.- InfoNetOLAP: OLAP and Mining of Information Networks.- Integrating Clustering with Ranking in Heterogeneous Information Networks Analysis.- Mining Large Information Networks by Graph Summarization.- Analysis of Biological Information Networks.- Finding High-Order Correlations in High-Dimensional Biological Data.- Functional Influence-Based Approach to Identify Overlapping Modules in Biological Networks.- Gene Reachability Using Page Ranking on Gene Co-expression Networks.

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Titolo: Link Mining
Casa editrice: Springer Verlag
Data di pubblicazione: 2010
Legatura: Hardcover
Condizione libro: New

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Yu, Philip S.; Han, Jiawei; Faloutsos, Christos
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Descrizione libro Springer, 2010. Hardcover. Condizione: Fine. This book is in excellent condition with a few colorless scuffs to the textblock and a hint of rubbing, niether are very significant. Overall, a handsome copy, nearly new. Codice articolo 905015

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Descrizione libro Springer, 2010. Condizione: Very Good. 1st Edition.. Ships from the UK. Former Library book. Great condition for a used book! Minimal wear. Codice articolo GRP97438385

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Descrizione libro Springer-Verlag New York Inc., United States, 2010. Hardback. Condizione: New. 2010 ed.. Language: English . Brand New Book. 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,especial lyfrom 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. Wewouldliketoconveyourappreciationtoallauthorsfortheirvaluab lec- 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. Codice articolo LIB9781441965141

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Descrizione libro Springer, 2010. Condizione: Good. A+ Customer service! Satisfaction Guaranteed! Book is in Used-Good condition. Pages and cover are clean and intact. Used items may not include supplementary materials such as CDs or access codes. May show signs of minor shelf wear and contain limited notes and highlighting. Codice articolo 1441965149-2-4

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Descrizione libro Springer-Verlag New York Inc., United States, 2010. Hardback. Condizione: New. 2010 ed.. Language: English . Brand New Book. 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,especial lyfrom 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. Wewouldliketoconveyourappreciationtoallauthorsfortheirvaluab lec- 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. Codice articolo LIB9781441965141

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