Discovering Associations among Semantic Links

被引：4
|
作者：
Zhang, Junsheng [1 ]
Wang, Huilin [1 ]
Sun, Yunchuan [2 ]
机构：
[1] Inst Sci & Tech Informat China, IT Support Ctr, Beijing, Peoples R China
[2] Beijing Normal Univ, Sch Econ & Business Adm, Beijing 100875, Peoples R China
来源：
WISM: 2009 INTERNATIONAL CONFERENCE ON WEB INFORMATION SYSTEMS AND MINING, PROCEEDINGS | 2009年
关键词：
semantic links; reasoning rule; association; relationship;
D O I：
10.1109/WISM.2009.49
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Semantic link network is a semantic data model to manage Web resources and semantic relations among them. Its nodes represent Web resources, and its semantic links between the nodes represent the semantic relations between the resources. This paper studies two kinds of associations between semantic link types (relationships): reasoning associations and statistical associations. We propose the approaches to calculating the two kinds of association degrees respectively. Besides, algorithms are developed to discover the statistical association rules. Association between semantic link types are useful in relational query in semantic link networks.
引用
收藏
页码：204 / +
页数：2
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