A novel method for expert finding in online communities based on concept map and PageRank

被引：40

作者：

Rafiei, Majid ^{[1
]}

Kardan, Ahmad A. ^{[2
]}

机构：

[1] Amirkabir Univ Technol, Dept Comp Engn & IT, Adv E Learning Lab, Tehran, Iran

[2] Amirkabir Univ Technol, Comp Engn & IT Dept, Tehran, Iran

来源：

HUMAN-CENTRIC COMPUTING AND INFORMATION SCIENCES | 2015年 / 5卷

关键词：

Expert finding; Online community; Concept map; Dijkstra's algorithm; Knowledge sharing; PageRank algorithm; PROFESSIONAL VIRTUAL COMMUNITIES; KNOWLEDGE; INTEGRATION; INTENTIONS;

D O I：

10.1186/s13673-015-0030-5

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

An online community is a virtual community where people can express their opinions and their knowledge freely. There are a great deal of information in online communities, however there is no way to determine its authenticity. Thus the knowledge which has been shared in online communities is not reliable. By determining expertise level of users and finding experts in online communities the accuracy of posted comments can be evaluated. In this study, a hybrid method for expert finding in online communities is presented which is based on content analysis and social network analysis. The content analysis is based on concept map and the social network analysis is based on PageRank algorithm. To evaluate the proposed method java online community was selected and then correlation between our results and scores prepared by java online community was calculated. Based on obtained results Spearman correlation for 11 subcategories of java online community using this method is 0.904, which is highly an acceptable value.

引用

页数：18

共 34 条

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