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Link Mining: Models, Algorithms, and Applications
. Ed(S): Yu, Philip S.; Han, Jiawei; Faloutsos, Christos
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Description for Link Mining: Models, Algorithms, and Applications
hardcover. This book offers detailed surveys and systematic discussion of models, algorithms and applications for link mining, focusing on theory and technique, and related applications: text mining, social network analysis, collaborative filtering and bioinformatics. Editor(s): Yu, Philip S.; Han, Jiawei; Faloutsos, Christos. Num Pages: 586 pages, 55 black & white tables, biography. BIC Classification: PSA; UNF; UY. Category: (P) Professional & Vocational. Dimension: 234 x 156 x 33. Weight in Grams: 2240.
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 ... Read more
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 ... Read more
Product Details
Format
Hardback
Publication date
2010
Publisher
Springer United States
Number of pages
586
Condition
New
Number of Pages
586
Place of Publication
New York, NY, United States
ISBN
9781441965141
SKU
V9781441965141
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15
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