Recommendation for Web services with domain specific context awareness

Construction of Web service recommendation systems for users has become an important issue in service computing area. Content-based service recommendation is one category of recommendation systems. The system recommends services based on functionality of the services. Current content-based approaches use syntactic or semantic methods to calculate the similarity. However, syntactic methods are insufficient in expressing semantic concepts and semantic content-based methods only consider basic semantic level. Further, the approaches do not consider the domain specific context in measuring the similarity. Thus, they have been failed to capture the semantic similarity of Web services under a certain domain and this is affected to the performance of the recommendation. In this paper, we propose domain specific context aware recommendation approach that uses support vector machine and domain data set from search engine in similarity calculation process. Experimental results show that our approach works efficiently.