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Books > Science & Mathematics > Biology, life sciences > Molecular biology
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Link Mining: Models, Algorithms, and Applications (Hardcover, 2010 ed.)
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Link Mining: Models, Algorithms, and Applications (Hardcover, 2010 ed.)
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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...
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