A Comparative Study of Expert Search Strategies in Online Social Networks

被引：2

作者：

Joung, Yuh-Jzer ^{[1
]}

Chen, Shy-Min ^{[1
]}

Wu, Chih-Chang ^{[1
]}

Chiu, Terry Hui-Ye ^{[1
]}

机构：

[1] Natl Taiwan Univ, Dept Informat Management, Taipei 10764, Taiwan

来源：

2013 IEEE 27TH INTERNATIONAL CONFERENCE ON ADVANCED INFORMATION NETWORKING AND APPLICATIONS (AINA) | 2013年

关键词：

Expert Seeking; Social Networks; Search Strategy; Profile-Based Search; Structure-Based Search; Hybrid-Based Search; SMALL-WORLD PROBLEM;

D O I：

10.1109/AINA.2013.86

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

Expert Seeking is a social network application that requires certain search strategies in the form of expert candidate-selection process. Assuming that no one in the network has the global knowledge, a query for expertise must be forwarded to, and between, candidates in order to reach the right person. During this candidate-selection process, a person determines whom to forward the query based only on the local information s/he knows. Two types of local information, actor profiles and structural attributes, may be used in devising search strategies. In this paper we conduct a comprehensive comparative study on search strategies using these types of information, as well as on search strategies using both types simultaneously to see if there is a synergy between them.

引用

下载

页码：960 / 967

页数：8

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