社会网络中专家查找的服务模式

Xiu Li, Jia-yu Ma, Yujiu Yang, Dongzhi Wang
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引用次数: 9

摘要

专家寻找解决的任务是找到合适的人与适当的知识或技能。目前的专家搜索算法通常使用语言模型来估计查询与候选支持文档之间的相关性。然而,语言模型有一个限制,即所有的查询词都应该出现在每个支持文档中,这导致一些真正的专家无法被搜索到。因此,在分析文本内容的过程中,我们考虑使用一种基于显式语义分析(ESA)的新模型来代替语言模型。随着互联网技术的发展,这并不是寻找专家的唯一途径。在现代社交媒体中,我们可以记录下人们的社会关系,这可能会为专家寻找任务提供帮助。一个简单的事实是:一个人与专家的联系将提供他是一个真正的专家的潜在证据。本文提出了一种兼顾文献内容和社会关系的专家检索服务模式。社交网络中的关系用于对给定主题的专家进行重新排名。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Service Mode of Expert Finding in Social Network
Expert finding addresses the task of finding the right person with the appropriate knowledge or skills. State-of-the-art expert finding algorithms usually estimate the relevance between the query and the support documents of candidates using language model. However, the language model has a limitation that all the query terms should occur in each support document, which results in some real experts cannot be searched. So for the process of analyzing textual content, we consider using a new model based on Explicit Semantic Analysis (ESA) rather than the language model. With the development of Internet technology, this is not the only way to find experts. In the modern social media, we can record person's social relationships which might be available for expert finding task. A simple truth is: a person's connections with experts will provide the potential evidence that he is a real expert. In this paper, we propose a new service pattern for expert finding that accounts for both documents' content and social relationships. The relationships in the social network are used in re-ranking experts on a given topic.
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