Research on web information retrieval based on vector space model

被引：3
|
作者：
Bo Ning, Zhang Ji [1 ]
机构：
[1] College of Information Science and Technology, Hainan University, Hainan, Haikou 570228, China
来源：
Journal of Networks | 2013年 / 8卷 / 03期
关键词：
Clustering - Full-text retrievals - Similarity retrieval - Text information retrievals - Vector space models - Web information retrieval - Web service discovery - Web Services discovery;
D O I：
10.4304/jnw.8.3.688-695
中图分类号：
学科分类号：
摘要：
Existing methods and technologies for Web services discovery mainly consist of two models: service matching based on grammar and based on semantics. With keywords service matching method, we introduce text information retrieval technology with vectors and concept lattice theory. Then a web service discovery algorithm using eigenvectors is put forward. It orders the Web services by correlation among the services in Web service subset. The services which have bigger correlation will get anterior places. According to this algorithm a Web service discovery system based on eigenvectors is designed. We give description to key modules of the system. At last the improved algorithm is compared to methods based on full-text retrieval and pure similarity retrieval. The results show it has better performance in accuracy and response. © 2013 ACADEMY PUBLISHER.
引用
收藏
页码：688 / 695
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