Data mining technique for expertise search in a special interest group knowledge portal

Wan Muhammad Zulhafizsyam Wan Ahmad, S. Sulaiman, U. K. Yusof
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Abstract

The Internet contributes to the development of electronic community (e-community) portals. Such portals become an indispensable platform for members especially for a Special Interest Groups (SIG) to share knowledge and expertise in their respective fields. Finding expertise over the e-community portal will help interested people and researchers to identify other experts, working in the same area. However, it is quite a cumbersome task to search such expertise in the portal. In order to find an expert, expertise data mining could be a solution to ease the search of experts. Performing effective data mining technique will help to analyze and measure expertise level accurately in a SIG portal. This paper proposes a method called Expertise Data Mining (EDM) that comprises a few techniques for expertise search in a SIG portal. It expects to improve the finding of experts among the members of a SIG e-community.
特殊兴趣群体知识门户中专业知识搜索的数据挖掘技术
互联网促进了电子社区门户网站的发展。这些门户网站成为成员,特别是特殊兴趣小组(SIG)成员在各自领域分享知识和专业知识的不可或缺的平台。在电子社区门户网站上寻找专业知识将有助于感兴趣的人和研究人员找到在同一领域工作的其他专家。然而,在门户中搜索此类专业知识是一项相当繁琐的任务。为了找到专家,专家数据挖掘可以成为一种简化专家搜索的解决方案。执行有效的数据挖掘技术将有助于在SIG门户中准确地分析和测量专业水平。本文提出了一种专业知识数据挖掘(EDM)方法,该方法包含了SIG门户中专业知识搜索的几种技术。它希望改善SIG电子社区成员中专家的发现。
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