Abstract: Existing service discovery methods calculate service relevance based on statistical probability mostly, which is not able to precisely reveal the semantic relevance between query and service. Aiming at this shortage, this paper presents a Web service discovery method based on Vector Space Model(VSM). WordNet is adopted to build synonym vector. Service description is segmented to service theme and service content. A new function is provided to compute the relevance between query and service. Prototype system based on this method is also realized. Experimental result shows that this method has higher precision and recall with harmonic mean remaining in 0.6 above.
Web service discovery,
Vector Space Model(VSM),