Exploiting User Tagging for Web Service Co-Clustering

Abstract

We propose a novel Web services clustering framework by considering the word distribution of WSDL documents and tags. Typically, tags are annotated to Web services by users for organization. In this paper, four strategies are proposed to integrate the tagging data and WSDL documents in the process of service clustering. Tagging data is inherently uncontrolled, ambiguous, and overly personalized. Two tag recommendation approaches are proposed to improve the tagging data quality and service clustering performance. Comprehensive experiments demonstrate the effectiveness of the proposed framework using a real-world dataset. INDEX TERMS Web service, WSDL documents clustering, co-clustering, tag recommendation.

Service Partition Method Based on Particle Swarm Fuzzy Clustering

“…Web service clustering work can be classified into two types: semantic web services and nonsemantic web services [13]. For the semantic web services, combine keywords extracted from the web service document languages (WSDL).…”

A Web Service Clustering Method Based on Semantic Similarity and Multidimensional Scaling Analysis

“…In addition, some scholars also used context-aware methods to improve service clustering [9,11]. Liang et al used tag information in WSDL document clustering to improve the clustering effect [12]. Considering the sparse semantics of WSDL documents, Gu et al used open data to increase semantic information before clustering [13].…”

“…Next, the matrix H � (h ij ) n×n is constructed according to equation (12). In equation ( 12), I n is an identity matrix of order n, E n is a square matrix of order n, and any element of matrix E n is 1.…”