Probabilistic latent semantic indexing
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Discovering user access pattern based on probabilistic latent factor model
ADC '05 Proceedings of the 16th Australasian database conference - Volume 39
Efficiently finding web services using a clustering semantic approach
Proceedings of the 2008 international workshop on Context enabled source and service selection, integration and adaptation: organized with the 17th International World Wide Web Conference (WWW 2008)
Improving Web Service Discovery by Using Semantic Models
WISE '08 Proceedings of the 9th international conference on Web Information Systems Engineering
Discovering web services based on probabilistic latent factor model
APWeb/WAIM'07 Proceedings of the joint 9th Asia-Pacific web and 8th international conference on web-age information management conference on Advances in data and web management
Dynamic tags for dynamic data web services
Proceedings of the 5th International Workshop on Enhanced Web Service Technologies
Service research challenges and solutions for the future internet
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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.