Name
Abstract | ||
|---|---|---|
The concept of Web services has become a widely applied paradigm in research and industry, with the number of services published on the Internet increasing rapidly over the last few years. Thus, service recommendation is becoming a challenging and time-consuming task due to large search space. Organizing the Web services into clusters is a one of very efficient approach for search space pruning process. In this paper, we proposed cluster-based service recommendation approach. User may want to interact with services that have similar functionalities, which they used to interact. Thus, we consider semantic similarity between services as one factor in the clustering process. Further, user may be interesting to identify the appropriate services to generate value-added service. Thus, we consider the association between services as the second factor. Our approach recommend services for currently invoked service using the generated clusters and services with better QoS values selected by a filtering process. Experimental results show that our approach works effectively. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/SCC.2016.52 | 2016 IEEE International Conference on Services Computing (SCC) |
Keywords | Field | DocType |
Web service recommendation,Service clustering,Web service similarity,Association rule | Service design,Services computing,Mobile QoS,World Wide Web,WS-Addressing,Computer science,WS-I Basic Profile,Differentiated service,Web service,WS-Policy | Conference |
ISSN | ISBN | Citations |
2474-8137 | 978-1-5090-2629-6 | 4 |
PageRank | References | Authors |
0.40 | 13 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Banage T. G. S. Kumara | 1 | 62 | 9.65 |
| Incheon Paik | 2 | 241 | 38.80 |
| T. H. A. S. Siriweera | 3 | 19 | 1.91 |
| Koswatte R. C. Koswatte | 4 | 16 | 3.11 |