A new method for profile identification using ontology-based semantic similarity

Abstract Recently, with the development of information technology, internet users are consuming and storing more data than ever before. This effect caused an explosion of data on the web. However, using the web to search for data that matches his expectations reflects his preferences. For this reason, several research have been developed to realize recommendation systems in various domains such as social networks, e-commerce, tourism, and others. The present document aims to treat and cover a new system in the domain of tourism in order to offer users of the system a set of interesting places and tourist sites according to their preferences. To this end, our work will focus on the design of a new profile identification method, and this method is based on a set of keywords as input. In the first step of our method, we find if there is a correspondence between these given keywords and the concepts of the ontology “DATAtourisme.” Otherwise, we define a semantic correspondence between these keywords and the concepts of the ontology using an external resource called (WordNet). Then, we store the most similar ontology concepts of “DATAtourisme” in a Composite Capability/Preference Profiles, which will be used to filter our interesting places and sights.

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