A technique for computer detection and correction of spelling errors
Communications of the ACM
Machine Learning
Naive (Bayes) at Forty: The Independence Assumption in Information Retrieval
ECML '98 Proceedings of the 10th European Conference on Machine Learning
Semantic enrichment of places: Ontology learning from web
International Journal of Knowledge-based and Intelligent Engineering Systems - Intelligent agents and services for smart environments
Expert Systems with Applications: An International Journal
Location-Sensitive tour guide services using the semantic web
KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part II
Semantic LBS: ontological approach for enhancing interoperability in location based services
OTM'06 Proceedings of the 2006 international conference on On the Move to Meaningful Internet Systems: AWeSOMe, CAMS, COMINF, IS, KSinBIT, MIOS-CIAO, MONET - Volume Part I
Using social media to find places of interest: a case study
Proceedings of the 1st ACM SIGSPATIAL International Workshop on Crowdsourced and Volunteered Geographic Information
Detecting Places of Interest Using Social Media
WI-IAT '12 Proceedings of the The 2012 IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technology - Volume 01
Discovering and Characterizing Places of Interest Using Flickr and Twitter
International Journal on Semantic Web & Information Systems
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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.