Data Source Recommendation for Building Mashup Applications

摘要：

The emergence of mashup is gaining tremendous popularity and its application can be seen in a large number of domains. Along with the development of mashup technology, several mashup editors have been produced by the industry which can assist users to build mashups. However, with the increasing service and information sources distributed across the entire web space, even an easy to use mashup editor for nonprogrammers is not sufficient. In this paper, we apply the item based top-JV recommendation algorithm which is widely used in e-Commerce area to recommend data source to the users while they are building mashups based on collected data of existing mashups. We also conduct experiment to evaluate the parameters of the recommendation algorithm and finally achieve very satisfactory results.

关键词： Web 2.0 Mashup Data Source Recommendation

作者: Jiawei Cao Chunxiao Xing

作者单位: Web and Software Technology Research Center Tsinghua University Bejing, China

会议类型: 国际会议

会议名称: 2010 Seventh Web Information System and Applications Conference(第七届全国web信息系统及其应用学术会议)

会议地点: 呼和浩特

会议语种:英文

页码: 220-224

在线出版日期: 2010-08-20（万方平台首次上网日期，不代表论文的发表时间）