Abstract
AbstractThis 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.KeywordsRecommender SystemSemantic SimilarityService DescriptionSemantic AnnotationSemantic DescriptionThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
