Ontology-based recommendation for points of interest retrieved from multiple data sources

Introduction of powerful mobile devices and increasing availability of online services make it possible to develop a wide range of mobile applications. Making recommendations to the users on their mobile devices based on their location is a well-known application area of location based services. In this work we introduce an ontology based approach to find reasonable recommendations for sites (Points of Interest) like restaurants, hotels, and touristic places. We extend an existing OWL ontology in order to keep semantic relationships between different site types. Our application populates this ontology with site instances collected from several data sources, namely Google Maps, GeoNames, DBpedia and a local database. During this integration process, solutions for ontology mapping, site categorization, and duplicate site detection are developed. The ontology is then used to make recommendations on a mobile augmented reality application based on user's inputs on his device.