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Enhancing Recommendations for Conference Participants with Community and Topic Modeling

§ For a researcher it is always important to increase his/her social capital and excel attheir research area. For this, conferences act as perfect medium where researchers meetand present their work. However, due to the structure of the conferences finding similarauthors or interesting talks is not obvious for the researchers. One of most importantobservation made from the conferences is, researchers tend to form communities withcertain research topics as the series of conferences progresses. These communitiesand their research topics could be used in helping researchers find their potentialcollaborators and in attending interesting talks. In this research we present the design and implementation of a recommender systemwhich is built to provide recommendation of authors and talks at the conferences.Various concepts like Social Network Analysis (SNA), context awareness, communityanalysis, and topic modeling are used to build the system. This system can beconsidered as an extension to the previous system CAMRS (Context Aware MobileRecommender System). CAMRS is a mobile application which serves the same purposeas the current system. However, CAMRS uses only SNA and context to providerecommendations. Current system, CAMRS-2, is also an Android application builtusing REST based architecture. The system is successfully is deployed, and as partof thesis the system is evaluated. The evaluation results proved CAMRS-2 providesbetter recommendations over its predecessor.

Identiferoai:union.ndltd.org:UPSALLA1/oai:DiVA.org:liu-88741
Date January 2013
CreatorsPasham, Bharath
PublisherLinköpings universitet, Databas och informationsteknik, Linköpings universitet, Tekniska högskolan
Source SetsDiVA Archive at Upsalla University
LanguageEnglish
Detected LanguageEnglish
TypeStudent thesis, info:eu-repo/semantics/bachelorThesis, text
Formatapplication/pdf
Rightsinfo:eu-repo/semantics/openAccess

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