Designing ontology-driven recommender systems for tourism

Abstract

Nowadays, Internet users may experience some difficulty in finding the information they need from the huge multitude of existingweb pages.Apossible solution to this problem might lie in delegating some of the search tasks to machines, or in other words, in building a SemanticWeb in which information could be processed automatically by intelligent software agents. Given the constantly increasing growth of the tourism industry, it might be particularly helpful to develop virtual assistants capable of planning trips on the basis of a user's interests. If so, adopting Semantic Web technologies would make it possible to provide a more customized service to each user and thus satisfy their requests better. Hypothesizing such a scenario, this chapter describes an adaptive recommender system which adopts a semantic approach to assist the user both in the travel planning phase and, on-site, during the trip. Finally, the software system provides a module that infers the user's interests and preferences using data mining techniques aimed at improving the quality of the suggestions made by the system. © Springer International Publishing Switzerland 2014.