TIIS (한국인터넷정보학회)
Current Result Document :
| 한글제목(Korean Title) |
Clustering and Recommendation for Semantic Web Service in Time Series |
| 영문제목(English Title) |
Clustering and Recommendation for Semantic Web Service in Time Series |
| 저자(Author) |
Yu Lei
Wang Zhili
Meng Luoming
Qiu Xuesong
|
| 원문수록처(Citation) |
VOL 08 NO. 08 PP. 2743 ~ 2762 (2014. 08) |
한글내용
(Korean Abstract) |
|
영문내용
(English Abstract) |
Promoted by cloud technology and new websites, plenty and variety of Web services are emerging in the Internet. Meanwhile some Web services become outdated even obsolete due to new versions, and a normal phenomenon is that some services work well only with other services of older versions. These laggard or improper services are lowering the performance of the composite service they involved in. In addition, using current technology to identify proper semantic services for a composite service is time-consuming and inaccurate. Thus, we proposed a clustering method and a recommendation method to deal with these problems. Clustering technology is used to classify semantic services according to their topics, functionality and other aspects from plenty of services. Recommendation technology is used to predict the possible preference of a composite service, and recommend possible component services to the composite service according to the history information of invocations and similar composite services. The experiments show that our clustering method with the help of Ontology and TF/IDF technology is more accurate than others, and our recommendation method has less average error than others in the series of missing rate. |
| 키워드(Keyword) |
Recommendation
clustering
composite service
semantic
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| 파일첨부 |
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