A probabilistic semantic approach for discovering web services | Zendy

Jiangang Ma | Zendy; Jinli Cao | Zendy; Yanchun Zhang | Zendy

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A probabilistic semantic approach for discovering web services

Author(s) -

Jiangang Ma,

Jinli Cao,

Yanchun Zhang

Publication year - 2007

Publication title -

citeseer x (the pennsylvania state university)

Language(s) - English

Resource type - Conference proceedings

DOI - 10.1145/1242572.1242776

Subject(s) - computer science , probabilistic latent semantic analysis , web service , probabilistic logic , service discovery , matching (statistics) , semantic web , information retrieval , social semantic web , world wide web , service (business) , ws i basic profile , semantic web stack , web modeling , artificial intelligence , web intelligence , statistics , mathematics , economy , economics

Service discovery is one of challenging issues in Service-Oriented computing. Currently, most of the existing service discovering and matching approaches are based on keywords-based strategy. However, this method is inefficient and time-consuming. In this paper, we present a novel approach for discovering web services. Based on the current dominating mechanisms of discovering and describing Web Services with UDDI and WSDL, the proposed approach utilizes Probabilistic Latent Semantic Analysis (PLSA) to capture semantic concepts hidden behind words in the query and advertisements in services so that services matching is expected to carry out at concept level. We also present related algorithms and preliminary experiments to evaluate the effectiveness of our approach.

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