Social Graph Generation & Forecasting using Social Network Mining

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IEEE

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info:eu-repo/semantics/restrictedAccess

Abstract

Considering the noticeable attraction of users to social networking sites, lots of research has been carried out to take advantage of the users’ information available in these sites. Knowledge mining techniques have been developed in order to extract valuable pieces of information from the users’ activities. This paper deals with a methodology to generate a social graph of users’ actions and predict the future social activities of the users based upon the existing relationships. This graph is updated dynamically based on the changes in the selected social network. The forecasting performed is based upon some predefined rules applied on the graph.

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Due to copyright restrictions, the access to the publisher version (published version) of this conference publication is only available via subscription. You may click URI (with DOI: 10.1109/COMPSAC.2009.110) and have access to the this paper through the publisher web site or online databases, if your Library or institution has subscription to the related journal or publication.

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Computer Software

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Computer Software and Applications Conference, 2009. COMPSAC '09. 33rd Annual IEEE International (Volume:2 )

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2

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