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Learning semantically-annotated routes for context-aware recommendations on map navigation systems

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Learning semantically-annotated routes for context-aware recommendations on map navigation systems

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dc.contributor.author Mocholí Agües, Jose Antonio es_ES
dc.contributor.author Jaén Martínez, Francisco Javier es_ES
dc.contributor.author Krynicki, Kamil Krzysztof es_ES
dc.contributor.author Catalá Bolós, Alejandro es_ES
dc.contributor.author Picón, Artzai es_ES
dc.contributor.author Cadenas, Alejandro es_ES
dc.date.accessioned 2014-02-03T08:48:09Z
dc.date.issued 2012-09
dc.identifier.issn 1568-4946
dc.identifier.uri http://hdl.handle.net/10251/35311
dc.description.abstract Modern technology has brought many changes to our everyday lives. Our need to be in constant touch with others has been met with the cellphone, which has become our companion and the convergence point of many technological advances. The combination of capabilities such as browsing the Internet and GPS reception has multiplied the services and applications based on the current location of the user. However, providing the user with these services has certain drawbacks. Although map navigation systems are the most meaningful way of displaying this information, the user still has to manually set up the filter in order to obtain a non-bloated visualization of the map and the available services. To tackle this problem, we present here a semantic multicriteria ant colony algorithm capable of learning the user's routes, including associated context information, and then predicting the most likely route a user is following, given his current location and context data. This knowledge could then be used as the basis for offering services related to his current (or most likely future) context data close to the path he is following. Our experimental results show that our algorithm is capable of obtaining consistent solutions sets even when multiple objective ontological terms are included in the process. es_ES
dc.description.sponsorship This work has been supported by the Spanish Ministry of Science and Innovation, Centre for the Development of Industrial Technology (CDTI) under the funding project CENIT-MIO! CENIT-2008 1019. en_EN
dc.format.extent 11 es_ES
dc.language Inglés es_ES
dc.publisher Elsevier es_ES
dc.relation Spanish Ministry of Science and Innovation, Centre for the Development of Industrial Technology (CDTI) [CENIT MIO! CENIT-2008 1019] es_ES
dc.relation.ispartof Applied Soft Computing es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Semantic search es_ES
dc.subject Context-awareness es_ES
dc.subject Ant colony optimization es_ES
dc.subject Ontologies es_ES
dc.subject.classification LENGUAJES Y SISTEMAS INFORMATICOS es_ES
dc.title Learning semantically-annotated routes for context-aware recommendations on map navigation systems es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1016/j.asoc.2012.05.010
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació es_ES
dc.description.bibliographicCitation Mocholi Agües, JA.; Jaén Martínez, FJ.; Krynicki, KK.; Catalá Bolós, A.; Picón, A.; Cadenas, A. (2012). Learning semantically-annotated routes for context-aware recommendations on map navigation systems. Applied Soft Computing. 12(9):3088-3098. doi:10.1016/j.asoc.2012.05.010 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion http://dx.doi.org/10.1016/j.asoc.2012.05.010 es_ES
dc.description.upvformatpinicio 3088 es_ES
dc.description.upvformatpfin 3098 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 12 es_ES
dc.description.issue 9 es_ES
dc.relation.senia 229986


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