Name
Abstract | ||
|---|---|---|
Web services partake in various types of interactions during their lifetime such as recommendation, substitution, and composition, hence giving rise to social behaviors. In this paper, we propose a socialaware approach for service communities. Communities are built around socially active services called leaders. The remaining services, called followers, use past interactions to elect their leaders and join communities. We introduce a clustering algorithm for multi-relation networks and define heuristics to identify community leaders and followers. We also define a new metric, called interoperability degree, to determine the degree to which members of a community are likely to socially interact. We conduct experiments to illustrate that leveraging social behaviors may help clump together services that are suited to interoperate. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1007/978-3-319-46295-0_50 | Lecture Notes in Computer Science |
Field | DocType | Volume |
Social behavior,Data mining,World Wide Web,Social network,Interoperability,Computer science,Heuristics,Web service,Cluster analysis | Conference | 9936 |
ISSN | Citations | PageRank |
0302-9743 | 1 | 0.36 |
References | Authors | |
8 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hamza Labbaci | 1 | 3 | 2.15 |
| Brahim Medjahed | 2 | 1077 | 73.34 |
| Youcef Aklouf | 3 | 11 | 3.52 |
| Zaki Malik | 4 | 501 | 34.83 |