BibSonomy publications for /author/Gil-SollaMon Aug 29 00:00:00 CEST 2011Inf. Sci.214823-4846Exploring synergies between content-based filtering and Spreading Activation techniques in knowledge-based recommender systems.1812011dblp Mon Aug 08 00:00:00 CEST 2011WISEconf/wise/2004415-421Lecture Notes in Computer ScienceAVATAR: An Advanced Multi-agent Recommender System of Personalized TV Contents by Semantic Reasoning.33062004dblp Thu Jul 07 00:00:00 CEST 2011ICSRconf/icsr/20041-10Lecture Notes in Computer ScienceSupporting Software Variability by Reusing Generic Incomplete Models at the Requirements Specification Stage.31072004dblp Thu Jul 07 00:00:00 CEST 2011ICWLconf/icwl/200483-90Lecture Notes in Computer ScienceTechnologies to Support Collaborative Learning over the Multimedia Home Platform.31432004dblp Wed Jul 06 00:00:00 CEST 2011Ershov Memorial Conferenceconf/ershov/2003366-380Lecture Notes in Computer ScienceImproving the Consistency Checking Process by Reusing Formal Verification Knowledge.28902003dblp Wed Jul 06 00:00:00 CEST 2011MIPSconf/mips/2003376-387Lecture Notes in Computer ScienceA Mixed XML-JavaBeans Approach to Developing T-learning Applications for the Multimedia Home Platform.28992003dblp Wed Jul 06 00:00:00 CEST 2011IFMconf/ifm/2004382-401Lecture Notes in Computer ScienceA Many-Valued Logic with Imperative Semantics for Incremental Specification of Timed Models.29992004dblp Tue Jul 05 00:00:00 CEST 2011ICWEconf/icwe/2003523-524Lecture Notes in Computer ScienceThe Multimedia Home Platform (MHP) Framework for Web Access through Digital TV.27222003dblp Tue Apr 26 00:00:00 CEST 2011Multimedia Tools Appl.1151-179TVGuide2.0: applying the Web2.0 fundamentals to IDTV.532011dblp Wed Feb 09 00:00:00 CET 2011Expert Syst. Appl.55289-5298User-generated contents and reasoning-based personalization: Ingredients for a novel model of mobile TV.382011dblp Fri Jan 14 15:04:03 CET 2011Lecture Notes Computer Science (Web Information Systems – WISE 2004)3306415--421AVATAR: An Advanced Multi-agent Recommender System of Personalized TV Contents by Semantic Reasoning2004TV-Anytime personalized recommender In this paper a recommender system of personalized TV contents, named AVATARWork supported by the Ministerio de Educación y Ciencia Research Project TSI2004-03677., is presented. We propose a modular multi-agent architecture for the system, whose main novelty is the semantic reasoning about user preferences and historical logs, to improve the traditional syntactic content search. Our approach uses Semantic Web technologies – more specifically an OWL ontology – and the TV-Anytime standard to describe the TV contents. To reason about the ontology, we have defined a query language, named LIKO, for inferring knowledge from properties contained in it. In addition, we show an example of a semantic recommendation by means of some LIKO operators.ER -Wed Oct 27 00:00:00 CEST 2010Expert Syst. Appl.96538-6546Context-aware personalization services for a residential gateway based on the OSGi platform.372010dblp Fri Oct 15 16:11:49 CEST 2010Computers \& Education3927 - 949Provision of distance learning services over Interactive Digital TV with MHP502008Architectures inference infotainment music personalization preference recommendation semantic user Mon Oct 04 10:07:43 CEST 2010Knowledge-Based Systems4305--320{A flexible semantic inference methodology to reason about user preferences in knowledge-based recommender systems}212008base inference knowledge preference semantic Mon Aug 16 00:00:00 CEST 2010SNPDconf/snpd/2010165-170Automatic Query Generation in Guided Systems: Natural Language Generation from Graphically Built Query.2010dblp Mon Aug 16 00:00:00 CEST 2010SNPDconf/snpd/20109-14Semantic Query Validation in Guided-Based Systems: Assuring the Construction of Queries that Make Sense.2010dblp Wed Jul 21 15:44:10 CEST 2010Expert Syst. Appl.21124-1133Enhancing TV programmes with additional contents using MPEG-7 segmentation information.372010dblp Wed Jul 21 15:42:01 CEST 2010Computer Communications7860-867Application-level assessment of approaches to coordinate node mobility in wireless sensor and actor networks.332010dblp Mon Mar 29 19:23:41 CEST 2010Multimedia Tools and Applications#feb#3407--436Receiver-side semantic reasoning for digital TV personalization in the absence of return channels412009recommender Abstract  Experience has proved that interactive applications delivered through Digital TV must provide personalized information to the viewers in order to be perceived as a valuable service. Due to the limited computational power of DTV receivers (eitherdomestic set-top boxes or mobile devices), most of the existing systems have opted to place the personalization engines indedicated servers, assuming that a return channel is always available for bidirectional communication. However, in a domainwhere most of the information is transmitted through broadcast, there are still many cases of intermittent, sporadic or nullaccess to a return channel. In such situations, it is impossible for the servers to learn who is watching TV at the moment,and so the personalization features become unavailable. To solve this problem without sacrificing much personalization quality,this paper introduces solutions to run a downsized semantic reasoning process in the DTV receivers, supported by a pre-selectionof material driven by audience stereotypes in the head-end. Evaluation results are presented to prove the feasibility of thisapproach, and also to assess the quality it achieves in comparison with previous ones.Wed Mar 17 15:41:32 CET 2010Lecture Notes Computer Science (Web Information Systems – WISE 2004)3306415--421AVATAR: An Advanced Multi-agent Recommender System of Personalized TV Contents by Semantic Reasoning2004hpi_ism10 recomender In this paper a recommender system of personalized TV contents, named AVATARWork supported by the Ministerio de Educación y Ciencia Research Project TSI2004-03677., is presented. We propose a modular multi-agent architecture for the system, whose main novelty is the semantic reasoning about user preferences and historical logs, to improve the traditional syntactic content search. Our approach uses Semantic Web technologies – more specifically an OWL ontology – and the TV-Anytime standard to describe the TV contents. To reason about the ontology, we have defined a query language, named LIKO, for inferring knowledge from properties contained in it. In addition, we show an example of a semantic recommendation by means of some LIKO operators. ER -