Volume 7 Number 5 (May. 2012)
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JSW 2012 Vol.7(5): 1022-1029 ISSN: 1796-217X
doi: 10.4304/jsw.7.5.1022-1029

Semantic Based Graph Mining Technology for Automatic Service Semantic Link Network Navigation

Anping Zhao1 and Yu Yu2
1College of Computer and Information Science, Chongqing Normal University, Chongqing, China
2College of Trade and Public Administration, Chongqing University, Chongqing, China

Abstract—To reduce the user's cognitive load and make sense of complex interlinked service data for realizing advanced service application, an approach to Service Semantic Link Network (S-SLN) navigation was proposed. Semantic based graph mining technology was employed as an effective solution for automatic service navigation. As one of the most important navigation tools, related service nodes recommendation was mapped as a basic graph mining problem. The closely related service nodes linked by different relations to form a sub-graph of S-SLN, which service nodes and links with different type and weight represent different service scenarios and relationship to the maximum extent such that sub-graph of S-SLN can improve or speed up user’s navigation decisions by providing the most probable related Web service and links which are most likely to be of interest. The experimental results and analysis shows that the proposed approach is efficient, feasible and practical.

Index Terms—semantic, graph mining, semantic link network, service navigation


Cite: Anping Zhao and Yu Yu, "Semantic Based Graph Mining Technology for Automatic Service Semantic Link Network Navigation," Journal of Software vol. 7, no. 5, pp. 1022-1029, 2012.

General Information

ISSN: 1796-217X (Online)
Frequency:  Bimonthly (Since 2020)
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, Google Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
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