Abstract
This work approaches the problem of discovering atomic web services that will realize complex business processes in an adaptive information system. It is proposed a model for semantic description of web services and user profile and the design of a semantic recommender engine based on this model. The recommender engine performs, during the web service discovery phase, a “similarity evaluation” step in which it can be possible to estimate the similarity between what the service offers and what the user prefers. A semantic algorithm, that measures distance between concepts in an ontology, is used to rank the results of the semantic matching between the user profile and a list of web services, suggesting to the user the most suitable services.
Cite
CITATION STYLE
Caforio, A., Corallo, A., Elia, G., & Solazzo, G. (2004). Service customization supporting an adaptive information system. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3215, pp. 342–349). Springer Verlag. https://doi.org/10.1007/978-3-540-30134-9_46
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