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Building Fexpert: System for searching experts in research university using K-MEANS algorithms

机译:Building Fexpert:使用K-MEANS算法搜寻研究型大学专家的系统

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摘要

In a research university, it is difficult to search for an expert since there are many faculties and staff who might work in multidisciplinary areas. Researchers who work in the same project might not always be from the same department. It is the objective of this study to develop a prototype of an expert finding system (Fexpert) for a research university. Data were undertaken from three sources: (1) researcher's personal profile, (2) graduate school profile and (3) research project profiles. The data were preprocessed and clustered according to each expert's keywords using K-Means algorithm. The proposed system can be used to find experts according to the cluster of their research or keywords. The statistical analysis summarizes records of researchers by their works and unit areas. This study can be further applied for an expert finding system of a large organization which might be a part of Knowledge Management.
机译:在研究型大学中,很难找到专家,因为有许多可能在跨学科领域工作的教职员工。在同一项目中工作的研究人员可能并不总是来自同一部门。这项研究的目的是为研究型大学开发专家发现系统(Fexpert)的原型。数据来自以下三个来源:(1)研究人员的个人资料,(2)研究生院的资料和(3)研究项目的资料。使用K-Means算法根据每个专家的关键词对数据进行预处理和聚类。所提出的系统可用于根据他们的研究集群或关键字来查找专家。统计分析按研究人员的工作和单位面积汇总了他们的记录。该研究可以进一步应用于大型组织的专家发现系统,该系统可能是知识管理的一部分。

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