Obiettivo "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." Campo scientifico natural sciencescomputer and information sciencesdata sciencedata miningnatural sciencescomputer and information sciencesartificial intelligencemachine learning Programma(i) FP7-PEOPLE - Specific programme "People" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013) Argomento(i) FP7-PEOPLE-2010-IEF - Marie-Curie Action: "Intra-European fellowships for career development" Invito a presentare proposte FP7-PEOPLE-2010-IEF Vedi altri progetti per questo bando Meccanismo di finanziamento MC-IEF - Intra-European Fellowships (IEF) Coordinatore TELEFONICA INVESTIGACION Y DESARROLLO SA Contributo UE € 166 180,80 Indirizzo RONDA DE LA COMUNICACION S/N DISTRITO C EDIFICIO OESTE I 28050 Madrid Spagna Mostra sulla mappa Regione Comunidad de Madrid Comunidad de Madrid Madrid Tipo di attività Private for-profit entities (excluding Higher or Secondary Education Establishments) Contatto amministrativo José Luis Peña Sedano (Mr.) Collegamenti Contatta l’organizzazione Opens in new window Sito web Opens in new window Costo totale Nessun dato