Finding Communities in Typed Citation Networks

dc.contributor.authorKroon, Frederick William
dc.date.accessioned2008-09-25T15:50:55Z
dc.date.available2008-09-25T15:50:55Z
dc.date.issued2008-09-25T15:50:55Z
dc.date.submitted2008
dc.description.abstractAs the Web has become more and more important to our daily lives, algorithms that can effectively utilize the link structure have become more and more important. One such task has been to find communities in social network data. Recently, however, there has been increased interest in augmenting links with additional semantic information. We examine link classification from the point of view of scientometrics, with an eye towards applying what has been learned about scientific citation to Web linking. Some community detection algorithms are reviewed, and one that has been developed for topical community finding on the Web is adapted to typed scientific citations.en
dc.identifier.urihttp://hdl.handle.net/10012/4037
dc.language.isoenen
dc.pendingfalseen
dc.publisherUniversity of Waterlooen
dc.subjectcitation classificationen
dc.subjectscientometricsen
dc.subjectsocial networksen
dc.subjectcommunity detectionen
dc.subjectbibliometricsen
dc.subjectinformation retrievalen
dc.subject.programComputer Scienceen
dc.titleFinding Communities in Typed Citation Networksen
dc.typeMaster Thesisen
uws-etd.degreeMaster of Mathematicsen
uws-etd.degree.departmentSchool of Computer Scienceen
uws.peerReviewStatusUnrevieweden
uws.scholarLevelGraduateen
uws.typeOfResourceTexten

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