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.
@InProceedings{CLEI-2015:144239,
author = {Alan De Renzis and Martin Garriga and Andres Flores and Alejandra Cechich and Alejandro Zunino},
title = {Case-based Reasoning for Web Service Discovery and Selection},
booktitle = {2015 XLI Latin American Computing Conference (CLEI), Special Edition},
pages = {25--36},
year = {2015},
editor = {Universidad Católica San Pablo},
address = {Arequipa-Peru},
month = {October},
organization = {CLEI},
publisher = {CLEI},
url = {http://clei.org/clei2015/144239},
isbn = {978-9972-825-91-0},
}