Efficient algorithms for finding maximum matching in graphs
ACM Computing Surveys (CSUR)
Determining Semantic Similarity among Entity Classes from Different Ontologies
IEEE Transactions on Knowledge and Data Engineering
An Information-Theoretic Definition of Similarity
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Semantic similarity of ontology instances tailored on the application context
ODBASE'06/OTM'06 Proceedings of the 2006 Confederated international conference on On the Move to Meaningful Internet Systems: CoopIS, DOA, GADA, and ODBASE - Volume Part I
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In this paper the problem of refining user queries on a trader of location-based services (LBSs) is faced by using two kinds of similarity (structural and semantic). LBSs typically concentrate on providing users with information about points of interest or on the support for navigation and routing tasks. Personalization is a key feature of LBSs that improves their usability and involves a process of gathering user information during interaction with the user. This information can be used to deliver appropriate content and services, tailor made to the user's needs. The approach proposed in the paper can be applied to any kind of location-based services, it is independent from the specific domain, it takes into account spatial information and, finally, it allows the user profiles to be acquired explicitly and implicitly.