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Personalized influential topic search via social network summarization (Extended abstract)

conference contribution
posted on 2017-05-16, 00:00 authored by Jianxin LiJianxin Li, Y Chen, C Liu, T Sellis, J X Yu, J S Culpepper
Social networks have become a vital mechanism to disseminate information to friends and colleagues. But the dynamic nature of information and user connectivity within these networks raised many new and challenging research problems. One of them is the query-related topic search in social networks. In this work, we investigate the important problem of the personalized influential topic search. There are two challenging questions that need to be answered: how to extract the social summarization of the social network so as to measure the topics' influence at the similar granularity scale? and how to apply the social summarization to the problem of personalized influential topic search. Based on the evaluation using real-world datasets, our proposed algorithms are proved to efficient and effective.

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Pagination

17 - 18

ISSN

1084-4627

ISBN-13

9781509065431

Publication classification

E3.1 Extract of paper

Title of proceedings

Proceedings - International Conference on Data Engineering

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