Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/478381
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dc.coverage.spatialComputer Science and Engineering
dc.date.accessioned2023-04-21T06:22:02Z-
dc.date.available2023-04-21T06:22:02Z-
dc.identifier.urihttp://hdl.handle.net/10603/478381-
dc.description.abstractAnalysis of complex network has emerged as a booming research area since last decade Social network a type of complex network has gained attention from the contemporary researchers due to the abundance of social network data in the Web in recent times Rapid increase in the number of subscribers to the social platforms such as blogs dating sites friends making sites provided by the Web has revealed unseen human relationships and motivated the researchers to make good use of this This t
dc.format.extentNot Available
dc.languageEnglish
dc.relationNot Available
dc.rightsself
dc.titleExploiting tie strength and structure towards link prediction in social networks
dc.title.alternativeNot available
dc.creator.researcherSett, Niladri
dc.subject.keywordComputer Science
dc.subject.keywordComputer Science Artificial Intelligence
dc.subject.keywordEngineering and Technology
dc.description.noteNot Available
dc.contributor.guideSingh, Sanasam Ranbir and Nandi, Sukumar
dc.publisher.placeGuwahati
dc.publisher.universityIndian Institute of Technology Guwahati
dc.publisher.institutionDepartment of Computer Science and Engineering
dc.date.registered2009
dc.date.completed2017
dc.date.awarded2017
dc.format.dimensionsNot Available
dc.format.accompanyingmaterialNone
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:Department of Computer Science and Engineering

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