Empirical Research on Search model of Web Service Repository

웹서비스 저장소의 검색기법에 관한 실증적 연구

  • Hwang, You-Sub (Department of Management Information Systems, College of Business Administration, University of Seoul)
  • 황유섭 (서울시립대학교 경영대학)
  • Received : 2010.10.17
  • Accepted : 2010.11.04
  • Published : 2010.12.31

Abstract

The World Wide Web is transitioning from being a mere collection of documents that contain useful information toward providing a collection of services that perform useful tasks. The emerging Web service technology has been envisioned as the next technological wave and is expected to play an important role in this recent transformation of the Web. By providing interoperable interface standards for application-to-application communication, Web services can be combined with component-based software development to promote application interaction and integration within and across enterprises. To make Web services for service-oriented computing operational, it is important that Web services repositories not only be well-structured but also provide efficient tools for an environment supporting reusable software components for both service providers and consumers. As the potential of Web services for service-oriented computing is becoming widely recognized, the demand for an integrated framework that facilitates service discovery and publishing is concomitantly growing. In our research, we propose a framework that facilitates Web service discovery and publishing by combining clustering techniques and leveraging the semantics of the XML-based service specification in WSDL files. We believe that this is one of the first attempts at applying unsupervised artificial neural network-based machine-learning techniques in the Web service domain. We have developed a Web service discovery tool based on the proposed approach using an unsupervised artificial neural network and empirically evaluated the proposed approach and tool using real Web service descriptions drawn from operational Web services repositories. We believe that both service providers and consumers in a service-oriented computing environment can benefit from our Web service discovery approach.

월드와이드웹 (WWW)은 유용한 정보를 포함하는 자료들의 집합에서 유용한 작업을 수행할 수 있는 서비스들의 집합으로 변화하고 있다. 새롭게 등장하고 있는 웹서비스 기술은 향후 웹의 기술적 변화를 추구하며 최근 웹의 변화에 중요한 역할을 수행할 것으로 기대된다. 웹서비스는 어플리케이션 간의 통신을 위한 호환성 표준을 제시하며 기업 내/외를 아우를 수 있는 어플리케이션 상호작용 및 통합을 촉진한다. 웹서비스가 서비스 지향 컴퓨팅환경으로서 운영하기 위해서는 웹서비스 저장소가 완성도 높게 구축되어 있어야 할 뿐 아니라, 사용자들의 필요에 맞는 웹서비스 컴포넌트를 찾을 수 있는 효율적인 도구들을 제공하여야 한다. 서비스 지향 컴퓨팅을 위한 웹서비스의 중요성이 증대됨에 따라 웹서비스의 발견을 효율적으로 지원할 수 있는 기법의 수요 또한 증대된다. 다수의 웹서비스 저장소들은 웹서비스 분류체계 및 검색기법들을 제안하여 왔지만, 대부분의 분류체계와 기존의 검색기법들은 실질적으로 활용하기에는 제대로 발달하지 못하였거나 지속적이고 체계적으로 관리하기에 너무 어려운 단점을 갖고 있다. 이 논문에서는 인공신경망 기반 군집화 기법과 XML 기반의 웹서비스 기술표준인 WSDL의 의미적 가치를 활용하여 웹서비스 분류체계 생성 프레임워크를 통한 복합 검색기법을 제안한다. 이 논문에서 인공신경망을 활용하여 제안하는 웹서비스 분류체계 생성 프레임워크는 실증적인 프로토타입 시스템으로 개발하였으며, 실제 운영되고 있는 웹서비스 저장소로부터 획득한 실제 웹서비스들을 사용하여 제안하는 웹서비스 복합 검색기법을 실증적으로 평가하였다. 또한 제안하는 방식의 효용성을 보여주는 의미 있는 실험결과를 보고한다.

Keywords

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