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LDA Hash Tagging Approach for Friend Recommendation in Micro blogging System

Author(s):

Sumit Mirase , Smt. Kashibai Navale college of engineering vadgaon (bk) , Pune.; Prof. N.P.Kulkarni, Smt. Kashibai Navale college of engineering vadgaon (bk) , Pune.

Keywords:

Microblogging, Temporal, Latent Dirichlet allocation, Semantic enrichment

Abstract

Because of the developing ubiquity and small frame the Microblogging is turning into people's most attractive choice for seeking the information and expressing opinions. Messages got by a user mainly rely on whom user follows. Therefore, recommending user with related interest may enhance the experience quality for information receiving. Since messages posted by Microblogging users reflect their hobbies or interest and the essential keywords in the messages show their primary focus to a huge extent, we can find users' preferences by investigating the user generated contents. Besides, user's hobbies, interest are not static; despite what might be required, they change as time proceeds by. In light of such instincts, we proposed a temporal-topic to analyze user's possible behavior’s and predict their potential friends in Microblogging. The model takes into users’ latent preferences by extracting keywords from aggregated messages over a stretch of time using a topic model, and after that, the effect of time is considered to deal interest.

Other Details

Paper ID: IJSRDV3I120530
Published in: Volume : 3, Issue : 12
Publication Date: 01/03/2016
Page(s): 552-556

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