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

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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

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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.