Name
Abstract | ||
|---|---|---|
Web Service discovery and selection deal with the retrieval of the most suitable Web Service, given a required functionality. Addressing an effective solution remains difficult when only functional descriptions of services are available. In this paper, we propose a solution by applying Case-based Reasoning, in which the resemblance between a pair of cases is quantified through a similarity function. We show the feasibility of applying Case-based Reasoning for Web Service discovery and selection, by introducing a novel case representation, learning heuristics and three different similarity functions. We also experimentally validate our proposal with a dataset of 62 real-life Web Services, achieving competitive values in terms of well-known Information Retrieval metrics. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1016/j.entcs.2016.02.006 | Electr. Notes Theor. Comput. Sci. |
Keywords | Field | DocType |
Web services,Service Selection,Service Discovery,Case-based Reasoning,Service Oriented Application | Data mining,Information retrieval,Computer science,WS-Addressing,Universal Description Discovery and Integration,Theoretical computer science,Web modeling,Heuristics,Service discovery,Web service,Case-based reasoning,WS-Policy | Journal |
Volume | Issue | ISSN |
321 | C | 1571-0661 |
Citations | PageRank | References |
2 | 0.40 | 22 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alan De Renzis | 1 | 19 | 3.81 |
| Martin Garriga | 2 | 64 | 7.87 |
| Andres Flores | 3 | 70 | 9.78 |
| Alejandra Cechich | 4 | 370 | 39.34 |
| Alejandro Zunino | 5 | 638 | 53.15 |