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El autor María del Carmen Rodríguez-Hernández ha publicado 3 artículo(s):

1 - A First Step Towards Keyword-Based Searching for Recommendation Systems

Due to the high availability of data, users are frequently overloaded with a huge amount of alternatives when they need to choose a particular item. This has motivated an increased interest in research on recommendation systems, which filter the options and provide users with suggestions about specific elements (e.g., movies, restaurants, hotels, news, etc.) that are estimated to be potentially relevant for the user. Recommendation systems are still an active area of research, and particularly in the last years the concept of context-aware recommendation systems has started to be popular, due to the interest of considering the context of the user in the recommendation process. In this paper, we describe our work-in-progress concerning pull-based recommendations (i.e., recommendations about certain types of items that are explicitly requested by the user). In particular, we focus on the problem of detecting the type of item the user is interested in. Due to its popularity, we consider a keyword-based user interface: the user types a few keywords and the system must determine what the user is searching for. Whereas there is extensive work in the field of keyword-based search, which is still a very active research area, keyword searching has not been applied so far in most recommendation contexts.

Autores: María del Carmen Rodríguez-Hernández / Francesco Guerra / Sergio Ilarri / Raquel Trillo / 
Palabras Clave: keyword-based search - mobile computing - recommendation systems

2 - Context-Aware Recommendations in Mobile Environments

Traditional recommendation systems offer relevant items (e.g., books, movies, music, etc.) to users, but they are not designed for mobile environments. In those environments, the context (e.g., the location, the time, the weather, the presence of other people, etc.) and the movements of the users may be important factors to obtain relevant and helpful recommendations. The emergence of context-aware recommendation systems has prompted the growth of recommendation algorithms that incorporate context information. However, most existing research in this field considers only static context information, despite the fact that exploiting dynamic context information would be very helpful in mobile computing scenarios. Moreover, the design and implementation of generic frameworks to support an easy development of context-aware recommendation systems has been relatively unexplored. In this paper, we present our ongoing work to develop a context-aware recommendation framework for distributed and mobile environments, which will allow suggesting relevant items to mobile users.

Autores: María del Carmen Rodríguez-Hernández / Sergio Ilarri / 
Palabras Clave: context-awareness - mobile computing - recommendation systems

3 - Definiendo un Caso de Estudio para Recomendaciones Dinámicas Móviles

Los denominados sistemas de recomendación permiten aliviar la sobrecarga de información de los usuarios, al ofrecer sugerencias específicas acerca de ítems concretos (películas, libros, actividades, puntos de interés, etc.) que pueden resultar de interés para el usuario. En los últimos años se está realizando una intensa investigación en el desarrollo de sistemas de recomendación sensibles al contexto, ya que tener en cuenta el contexto del usuario (posición geográfica, tiempo atmosférico, estado de ánimo, etc.) permite ofrecer recomendaciones más apropiadas. En entornos de computación móvil uno de los elementos clave del contexto del usuario es su localización, siendo relevante ofrecer sugerencias al usuario de forma proactiva (sin peticiones expresas por parte del usuario) y teniendo en cuenta su trayectoria. En este artículo, describimos nuestro trabajo en progreso relacionado con las recomendaciones dinámicas sensibles al contexto en entornos móviles. Debido a la dificultad de evaluación de estos sistemas de recomendación en el mundo real, nos centramos en el desarrollo de un caso de estudio que simulará un escenario para recomendaciones dinámicas para los visitantes de un museo.

Autores: María Del Carmen Rodríguez-Hernández / Sergio Ilarri / Ramon Hermoso / Raquel Trillo-Lado / 
Palabras Clave: computación móvil - Contexto - recomendaciones dinámicas