发现虚拟社区中的核心成员对于社区数据挖掘等应用问题有着相当重要的应用价值。为解决该问题,作者首先分析了一些虚拟社区中成员的兴趣相似性分布情况,从中发现核心成员间的兴趣存在相对较高的相似性。据此,作者提出了基于兴趣集中性的核心成员求解算法,并在豆瓣网的虚拟社区中进行了实验分析,实验结果证明了算法的有效性。
Abstract
The detection of core members in the virtual communities is of great value for many applications, e.g. community mining. To solve this issue, this paper first analyzes the distribution of interest similarity among the community members, finding that the interest profiles of those core members are more similar to each other than those occasional members. Therefore, an algorithm is proposed to detection the core members in virtual communities by interest clustering. This algorithm is evaluated in a real world data set from Douban.com, and produces satisfactory results.
关键词
计算机应用 /
中文信息处理 /
虚拟社区 /
核心成员 /
兴趣相似性
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Key words
computer application /
Chinese information processing /
virtual community /
core members /
interest similarity
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参考文献
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脚注
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基金
国家973计划资助项目(2004CB318109);国家863计划资助项目(2007AA01Z416)
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