Finding Experts Using Social Network Analysis

Yupeng Fu, Rongjing Xiang, Yiqun Liu, Min Zhang, Shaoping Ma
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引用次数: 73

Abstract

Searching an organization's document repositories for experts is a frequently occurred problem in intranet information management. A common method for finding experts in an organization is to use social networks - people are not isolated but connected by various kinds of associations. In organizations, people explicitly send email to one another thus social networks are likely to be contained in the patterns of communication. Moreover, in some web pages, the relationship among people is also recorded. In our approach we propose several strategies in discovering the associations among people from emails and web pages. Based on the social networks, we proposed an expertise propagation algorithm: from a ranked list of candidates according to their probability of being expert for a certain topic, we select a small set of the top ones as seed, and then use the social networks among the candidates to discover other potential experts. The experiments on TREC enterprise track show significant performance improvement with the algorithm.
使用社会网络分析寻找专家
在组织的文档库中搜索专家是内部网信息管理中经常出现的问题。在组织中寻找专家的一种常用方法是利用社会网络——人们不是孤立的,而是通过各种各样的协会联系在一起的。在组织中,人们明确地相互发送电子邮件,因此社交网络很可能包含在通信模式中。此外,在一些网页上,人与人之间的关系也被记录下来。在我们的方法中,我们提出了从电子邮件和网页中发现人们之间联系的几种策略。在社交网络的基础上,提出了一种专家传播算法:根据某一主题的专家概率,从候选名单中选出一小部分排名前几位的专家作为种子,然后利用候选名单中的社交网络发现其他潜在专家。在TREC企业轨道上的实验表明,该算法的性能有了显著提高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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