企业专家搜索:结合文本和社会网络分析

Kate Ehrlich, Ching-Yung Lin, Vicky Griffiths-Fisher
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引用次数: 184

摘要

员工依赖于企业中的其他人来快速获取重要信息。但是,目前寻找专家的系统并没有充分解决寻找陌生人并与之交谈的社会影响。本文提供了SmallBlue的用户研究,SmallBlue是一个社会上下文感知的专家搜索系统,可用于识别专家,查看动态个人资料信息,并获得与专家的社会距离信息,然后决定是否以及如何发起联系。该系统采用一种创新的隐私保护方法,从电子邮件和聊天记录中推断内容和动态社交网络。我们描述了SmallBlue的用法,并讨论了下一代企业级寻人系统的含义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Searching for experts in the enterprise: combining text and social network analysis
Employees depend on other people in the enterprise for rapid access to important information. But current systems for finding experts do not adequately address the social implications of finding and engaging strangers in conversation. This paper provides a user study of SmallBlue, a social-context-aware expertise search system that can be used to identify experts, see dynamic profile information and get information about the social distance to the expert, before deciding whether and how to initiate contact. The system uses an innovative approach to privacy to infer content and dynamic social networks from email and chat logs. We describe usage of SmallBlue and discuss implications for the next generation of enterprise-wide systems for finding people.
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