Team Formation in Social Networks based on Local Distance Metric

被引：0

作者：

Ashenagar, Bahareh ^{[1
]}

Eghlidi, Negar Foroutan ^{[1
]}

Afshar, Ardavan ^{[1
]}

Hamzeh, Ali ^{[1
]}

机构：

[1] Shiraz Univ, Dept Comp Sci & Engn & IT, Shiraz, Iran

来源：

2015 12TH INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS AND KNOWLEDGE DISCOVERY (FSKD) | 2015年

关键词：

social networks; team formation; expert team;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

The tremendous growth of social networking in last decades has resulted in an extensive research into this area. Social network users are enabled to easily communicate and collaborate with each other. Due to the significant role of network users, a new research topic in social networking analysis is team formation. The social network is modeled as a graph where nodes represent experts and edges show the initial collaborations between experts. The present research aims to tackle the problem to find an expert team in social network in order to complete a project that requires a set of skills. An algorithm is thus proposed to find the best suited team for the assigned project: a new method is devised as well to determine the distance between pairs of experts. Experimental results on DBLP dataset present the efficiency of our proposed method.

引用

页码：946 / 952

页数：7

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