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problem that needs to be addressed. Most existing related work employed keyword-based method to search services and focused on matching users' queries with semantic or syntactic Web service description. They seldom took advantage of relationships between services to improve the performance of service searching. This paper
as the services management. Existing methods for Web services clustering mostly focus on utilizing directly key features from WSDL documents, e.g., input/output parameters and keywords from description text. Probabilistic topic model Latent Dirichlet Allocation (LDA) is also adopted, which extracts latent topic features
and user behaviors are indexed and managed; Based on the user's input keywords and navigation context, a group of relevant services are dynamically searched, ranked and recommended for facilitating future navigations; the service navigation is smoothed by a web2.0 style exploratory user interface. A prototype system is
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.