WS-SCAN:A Effective Approach for Web Services Clustering
With the rapid growth of available web services developed by different organizations, clustering of web services is required for conveniently managing services such as web services selection, discovery, composition and QoS prediction. However, the traditional clustering approaches have some drawbacks in similarity measuring and information preprocessing. In this paper, a similarity model is presented to measure the similarity between web services. Based on this model, a special preprocessing approach is proposed, which considers the programming style and naming rules. The proposed approach is combined with the SCAN algorithm and evaluated through the planned experiments. The experimental results show that the proposed model and approach can effectively improve clustering of web services and further improve the web service-based applications such as service discovery, composition and QoS prediction.
web service clustering information preprocessing similarity measure
Zhiliang Zhu Haitao Yuan Jie Song Jing Bi Guoqi Liu
College of Software, Northeastern University Dept.of Information Science and Engineering, Northeastern University Shenyang, P.R.China
国际会议
太原
英文
618-622
2010-10-22（万方平台首次上网日期，不代表论文的发表时间）