Knowledge Recommendation Based on Social Network Theory

被引：0
|
作者：
Fan, Bei [1 ]
Liu, Lu [1 ]
Li, Ming [1 ]
Wu, Yin [1 ]
机构：
[1] BeiHang Univ, Sch Econ & Management, Beijing, Peoples R China
来源：
2008 IEEE SYMPOSIUM ON ADVANCED MANAGEMENT OF INFORMATION FOR GLOBALIZED ENTERPRISES, PROCEEDINGS | 2008年
关键词：
Knowledge Recommendation; Social Network Analysis; Centralization Analysis; Cohesive Subgroup Analysis;
D O I：
暂无
中图分类号：
F [经济];
学科分类号：
02 ;
摘要：
In Knowledge Management Systems (KMS), the overabundance of information has forced users to spend more time searching for information that they need. If KMS can discover users' interests and initiatively recommend knowledge which users are interested in, it will greatly improve users' satisfaction. In this paper, based on social network theory, we propose a new method for establishing a knowledge network by analyzing users' retrieval records. With the network, we introduce an algorithm which is based on centralization analysis and cohesive subgroup analysis in social network theory to meet the requirements of recommendation. The success in a practical project demonstrates the effectiveness of the method.
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页码：322 / 324
页数：3
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