Discovering the best web service: A neural network-based solution

Differentiating between Web services that share similar functionalities is becoming a major challenge into the discovery of Web services. In this paper we propose a framework for enabling the efficient discovery of Web services using Artificial Neural Networks (ANN) best known for their generalization capabilities. The core of this framework is applying a novel neural network model to Web services to determine suitable Web services based on the notion of the Quality of Web Service (QWS). The main concept of QWS is to assess a Web service\u27s behaviour and ability to deliver the requested functionality. Through the aggregation of QWS for Web services, the neural network is capable of identifying those services that belong to a variety of class objects. The overall performance of the proposed method shows a 95% success rate for discovering Web services of interest. To test the robustness and effectiveness of the neural network algorithm, some of the QWS features were excluded from the training set and results showed a significant impact in the overall performance of the system. Hence, discovering Web services through a wide selection of quality attributes can considerably be influenced with the selection of QWS features used to provide an overall assessment of Web services. ©2009 IEEE

WWW 2007 / Poster Paper Topic: Services Crawling Multiple UDDI Business Registries

As Web services proliferate, size and magnitude of UDDI Business Registries (UBRs) are likely to increase. The ability to discover Web services of interest then across multiple UBRs becomes a major challenge specially when using primitive search methods provided by existing UDDI APIs. Clients do not have the time to endlessly search accessible UBRs for finding appropriate services particularly when operating via mobile devices. Finding services of interest should be time effective and highly productive. This paper addresses issues relating to the efficient access and discovery of Web services across multiple UBRs and introduces a novel exploration engine, the Web Service Crawler Engine (WSCE). WSCE is capable of crawling multiple UBRs, and enables for the establishment of a centralized Web services repository that can be used for discovering Web services much more efficiently. The paper presents experimental validation, results, and analysis of the proposed ideas. Categories and Subject Descriptors D.2.12 [Software Engineering]: Interoperability – data mapping, distributed objects, interface definition languages; H.3.