Based on analyzing closeness and authority for ranking expert in social network

Authors:
Ling Jin;Jae Yeol Yoon;Young Hee Kim;Ung Mo Kim
Affiliations:
Database Laboratory, Information and Communication Engineering, SungKyunKwan University, Suwon, Korea;Database Laboratory, Information and Communication Engineering, SungKyunKwan University, Suwon, Korea;Database Laboratory, Information and Communication Engineering, SungKyunKwan University, Suwon, Korea;Database Laboratory, Information and Communication Engineering, SungKyunKwan University, Suwon, Korea
Venue:
ICIC'11 Proceedings of the 7th international conference on Advanced Intelligent Computing Theories and Applications: with aspects of artificial intelligence
Year:
2011

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Abstract

As the popularity of Web 2.0 increases, web users used to establish communication relationships and share resources with others online. Recently, one important research for retrieving information from the web has become a major issue. Moreover, due to the social network popularity, there is much more opportunity to find out various human resources to help people get what they want. In our work, we propose to help the social network users to find out the most reachable experts who are authorized researchers on a common topic area with the users. For this purpose, we propose how to calculate centrality closeness from requesting user to experts, analyze the relevancy of an expert to the topic, and finally combine both of the result to rank the most reachable experts for the requesting user.