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}, }