DocumentCode
1421953
Title
Building Association Link Network for Semantic Link on Web Resources
Author
Luo, Xiangfeng ; Xu, Zheng ; Yu, Jie ; Chen, Xue
Author_Institution
High Performance Comput. Center, Shanghai Univ., Shanghai, China
Volume
8
Issue
3
fYear
2011
fDate
7/1/2011 12:00:00 AM
Firstpage
482
Lastpage
494
Abstract
Association Link Network (ALN) aims to establish associated relations among various resources. By extending the hyperlink network World Wide Web to an association-rich network, ALN is able to effectively support Web intelligence activities such as Web browsing, Web knowledge discovery, and publishing, etc. Since existing methods for building semantic link on Web resources cannot effectively and automatically organize loose Web resources, effective Web intelligence activities are still challenging. In this paper, a discovery algorithm of associated resources is first proposed to build original ALN for organizing loose Web resources. Second, three schemas for constructing kernel ALN and connection-rich ALN (C-ALN) are developed gradually to optimize the organizing of Web resources. After that, properties of different types of ALN are discussed, which show that C-ALN has good performances to support Web intelligence activities. Moreover, an evaluation method is presented to verify the correctness of C-ALN for semantic link on documents. Finally, an application using C-ALN to organize Web services is presented, which shows that C-ALN is an effective and efficient tool for building semantic link on the resources of Web services.
Keywords
Web services; data mining; semantic Web; Web browsing; Web intelligence activities; Web knowledge discovery; Web resources; Web services; association link network; association rich network; connection rich ALN; hyperlink network World Wide Web; kernel ALN; semantic link; Association rules; Knowledge engineering; Petroleum; Resource description framework; Semantics; Web pages; Web services; Association link network (ALN); intelligent browsing; interactive computing; knowledge discovery; semantic Web;
fLanguage
English
Journal_Title
Automation Science and Engineering, IEEE Transactions on
Publisher
ieee
ISSN
1545-5955
Type
jour
DOI
10.1109/TASE.2010.2094608
Filename
5682368
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