Recommendation of Tourist Points of Interest using the Web as source

Este artículo presenta un sistema de recomendación híbrido, basado en contenido y comunidad de usuarios, para recomendar a los usuarios los lugares próximos más afines a sus gustos. El contenido se extrae de forma automática de la web oficial del punto de interés. Destacamos los buenos resultados obtenidos cuando la información recuperada para cada lugar de su sitio web es descriptiva. Nuestros experimentos se han realizado sobre los datos ofrecidos por la organización del Contextual Suggestion Track en TREC 2014, una tarea exigente donde la información de los usuarios es dispersa y cuyas recomendaciones se deben obtener a partir de coordenadas geográficas y poca información adicional.This paper introduces a hybrid recommender system, based on both content and community of users, to suggest places according to user's interests. The content has been automatically extracted from official web page of each place. We remark the promising results obtained when the official web site provides descriptive content. Our experiments have been performed on the Contextual Suggestion Track dataset from TREC 2014, a competitive task where information about users is very sparse and recommendations must come from only GPS coordinates and few additional information.Este trabajo se ha desarrollado gracias a la financiación parcial del proyecto ATTOS (TIN2012-38536-C03-0) del Gobierno de España y del proyecto CEATIC-2013-01 de la Universidad de Jaén

Suggestion contextuelle composite

International audienceLa suggestion contextuelle consiste à recommander à un utilisateur un ensemble de lieux d'activités adaptés à ses préférences et à son contexte. La plupart des approches existantes considèrent uniquement ces deux caractéristiques pour constituer leur liste de suggestions. Cependant, les recherches en systèmes de recommandation ont récemment souligné l'importance de la diversité des suggestions. Cet article présente un modèle novateur de suggestion contextuelle inspiré de la recherche composite qui consiste à regrouper les suggestions en différentes grappes thématiquement cohésives. L'évaluation réalisée dans le cadre de la piste Contextual Suggestion de TREC 2013 et 2014 montre que notre approche est compétitive et permet d'améliorer la diversité des suggestions sans dégrader leur pertinence

An Evaluation of Contextual Suggestion

This thesis examines techniques that can be used to evaluate systems that solve the complex task of suggesting points of interest to users. A traveller visiting an unfamiliar, foreign city might be looking for a place to have fun in the last few hours before returning home. Our traveller might browse various search engines and travel websites to find something that he is interested in doing, however this process is time consuming and the visitor may want to find some suggestion quickly. We will consider the type of system that is able to handle this complex request in such a way that the user is satisfied. Because the type of suggestion one person wants will differ from the type of suggestion another person wants we will consider systems that incorporate some level of personalization. In this work we will develop user profiles that are based on real users and set up experiments that many research groups can participate in, competing to develop the best techniques for implementing this kind of system. These systems will make suggestion of attractions to visit in various different US cities to many users. This thesis is divided into two stages. During the first stage we will look at what information will go into our user profiles and what information we need to know about the users in order to decide whether they would visit an attraction. The second stage will be deciding how to evaluate the suggestions that various systems make in order to determine which system is able to make the best suggestions