Alberto Díaz Esteban

Evaluating a User-Model Based Personalisation Architecture for Digital News Services

An architecture that provides personalised filtering and dissemination of news items is presented. It is based on user profiles and it provides mechanisms that allow the user to control and tailor to his own needs the interaction between three different sources of relevance judgements: the existing newspaper categorisation by sections, basic information retrieval on user selected keywords, and an additional operation of automatic categorisation against an alternative hierarchy of categories. These three tiers cover some of the most promising access methods for digital libraries. The proposed architecture has been implemented and evaluation results are presented, covering user response, system efficiency, and user preferences regarding the set of methods made available to them.

A User Model Based on Content Analysis for the Intelligent Personalization of a News Service

In this paper we present a methodology designed to improve the intelligent personalization of news services. Our methodology integrates textual content analysis tasks to achieve an elaborate user model, which represents separately short-term needs and long-term multi-topic interests. The characterization of users interests includes his preferences about content, using a wide coverage and non-specific-domain classification of topics, and structure (newspaper sections). The application of implicit feedback allows a proper and dynamic personalization.

Integrating Multilingual Text Classification Tasks and User Modeling in Personalized Newspaper Services

In this paper a methodology designed to improve the intelligent personalization of newspaper services is presented. The methodology integrates textual content analysis tasks to achieve an elaborate user model, which represents separately short-term needs and long-term multi-topic interests. The characterization of users interests includes his preferences about structure, content and information delivery. A wide coverage and non-specific-domain classification of topics and a personal set of keywords allow the user to define his preferences about content. The application of implicit feedback allows a proper and dynamic personalization. Another topic that have been addressed in the thesis is the evaluation of systems offering to send users a selection of the daily news by electronic mail. Finally, the extensions to a multilingual framework are studied.