Research And Implementation Of WEB Service Searching Based On New Words Discoverys

Nowadays,there are lots of resource and information exposed on the Internet networks.Therefore,networks which are becoming increasingly convergent and open tend to bring about more complexity in plenty of Web services.It is significant to find a good method to enhance Web service searching which applied to Web service reuse and Web service composition.Traditional methods is basing on syntax searching.The information losing leads to the low accuracy in the searching process for lack of semantic searching.On the other hand,semantic description of Web services uses semantic web technology to enhance machine's understanding ability,but there are a number of Web services do not contain semantic description which causes lower search performance.This thesis proposes a new method which uses query log to solve the essential problem mentioned above.The new method uses new words discovered from some big data or large amount of context,which come from query log,to make a detailed semantic analysis with query text about Web service matching for finding new words and their semantic relations.On the other hand,this thesis utilizes the description of Web services to build Web service description model which can shield the difference between types of Web service.Besides,this thesis applies statistical method with the analysis of query text to compute the semantic distance of words to be matched.The algorithm of computing Web service match degree is designed to solve the problem which is difficult for traditional matching in the brief and pure semantic description of Web service.Eventually,this thesis designs and implements the algorithm of the Web service searching combined with new words.New words is designed to offer help the query text analysis and semantic searching.In contrast to traditional researches,Web service search based on new words discovery has improvements in the accuracy and the recall rate.