Title :
Discovering Associations among Semantic Links
Author :
Zhang, Junsheng ; Wang, Huilin ; Sun, Yunchuan
Author_Institution :
IT Support Center, Inst. of Sci. & Tech. Inf. of China, Beijing, China
Abstract :
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.
Keywords :
Internet; data mining; data models; statistical analysis; Web resources; associations discovery; reasoning associations; semantic data model; semantic link network; semantic link types; semantic relations; statistical association rules; Association rules; Conference management; Data models; Economic forecasting; Information retrieval; Management information systems; Resource management; Search engines; Semantic Web; Sun; association; reasoning rule; relationship; semantic links;
Conference_Titel :
Web Information Systems and Mining, 2009. WISM 2009. International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-0-7695-3817-4
DOI :
10.1109/WISM.2009.49
