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
收藏
页码：960 / 967
页数：8
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