Objective "Recommender Systems have become essential personalized navigational tools for usersto wade through the plethora of online content as they allow users todiscover relevant information that they would have never known itexisted. In recent years, the importance of this information discoveryprocess as opposed to explicit (keyword-based) search has been emphasized.Current research in Recommender Systems, while taking into account therelation between user and item, often ignores the ``context'' of therecommendation. We define as ``context'' any environmental, temporalor otherwise variable that influences a decision a user might make.Early work on Context-Aware Recommender Systems (CARS) has found thatcontextual factors do influence the recommendation needs of users.However, the role that each of the contextual variables (e.g. time,location, activity, emotional state, social network, etc.) plays onthe user's needs is still not clearly defined.The main aim of this proposal is to build a compact Context-AwareRecommender System (CARS) for mobile and desktop computing devices.The research methodology of this proposal is structured in 3 researchobjectives:1) Understanding contextual information in Recommender SystemsWhere data will be mined in order to uncover underlyingpatterns in the influence of context on users' preferences.2) Building Context-aware Recommendation modelsWhich involves using state of the art Machine Learning to buildmodels and algorithms for CARS3) Building a prototype and deploymentWhich involves building and deploying a prototype based on thedeveloped algorithms and conducting a user studyModern Machine Learning algorithms have been shown to perform well inRecommendation Tasks and this proposal has a strong algorithmic andmethods focus but also aims at knowledge discovery both through DataMining and Human Computer Interaction techniques." Fields of science natural sciencescomputer and information sciencesdata sciencedata miningnatural sciencescomputer and information sciencesartificial intelligencemachine learning Programme(s) FP7-PEOPLE - Specific programme "People" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013) Topic(s) FP7-PEOPLE-2010-IEF - Marie-Curie Action: "Intra-European fellowships for career development" Call for proposal FP7-PEOPLE-2010-IEF See other projects for this call Funding Scheme MC-IEF - Intra-European Fellowships (IEF) Coordinator TELEFONICA INVESTIGACION Y DESARROLLO SA EU contribution € 166 180,80 Address RONDA DE LA COMUNICACION S/N DISTRITO C EDIFICIO OESTE I 28050 Madrid Spain See on map Region Comunidad de Madrid Comunidad de Madrid Madrid Activity type Private for-profit entities (excluding Higher or Secondary Education Establishments) Administrative Contact José Luis Peña Sedano (Mr.) Links Contact the organisation Opens in new window Website Opens in new window Total cost No data