Gustavo González

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The ability to express and recognise emotions is a fundamental element of human social interaction. With regard to web services, user requirements can be forgotten and forsaken when the user's emotional needs are satisfied. The question, then, is how to improve recommender systems, and make them more pleasant to the user through the perception of his/her(More)
This paper describes our approach to the next generation of open, distributed and heterogeneous recommender systems using Smart User Models (SUM). Our work focuses on integrating multiple agent-based services based on a unique representation of the user in what is called a Multi-agent Smart User Model. Intelligent agents are used in order to obtain a single(More)
Emotions are crucial for user's decision making in recommendation processes. We first introduce ambient recommender systems, which arise from the analysis of new trends on the exploitation of the emotional context in the next generation of recommender systems. We then explain some results of these new trends in real-world applications through the smart(More)
Our research focuses on the development of methodologies that take into account the human factor in user models. There is an obvious link between personality traits and user preferences-both being indications of default tendencies in behavior, that can be automated by systems that recommend items to a user. In this work, we define an emotional component for(More)
This research focuses on the development of methodologies of tourism-related integration services. The authors define an adaptive Smart User Model and develop a methodology to build and manage this Smart User Model in the next generation of open environments in order to offer the user a variety of highly personalized services. In addition, the Smart User(More)
Smart User Models improve the quality of services person-alization reducing the overload of processed information and capturing the affectivity of the user in the next generation of open, distributed and networked environments in Ambient Intelligence. In this paper, we combine the flexibility of intelligent agents with the information processing(More)
Smart User Models improve the quality of service person-alization, they reduce the overload of processed information and can establish the user's preferences and emotional state in the next generation of open, distributed and networked environments in Ambient Intelligence. In this paper, we combine the flexibility of intelligent agents with the information(More)
The objective of this paper is twofold. The first is to develop a methodology capable of extracting the Human Values Scale (HVS) from the user, with reference to his/her objective, subjective and emotional features, in order to improve the adaptation of user models to open environments, particularly in recommender systems. For this purpose a Coherence(More)
Integrated Vehicle Health Management (IVHM) systems on modern aircraft or autonomous unmanned vehicles should provide diagnostic and prognostic capabilities with lower support costs and amount of data traffic. When mission objectives cannot be reached for the control system since unanticipated operating conditions exists, namely a failure, the mission plan(More)
We first introduce ambient recommender systems, which arose from the analysis of new trends in human factors in the next generation of recommender systems. We then explain some results of these new trends in real-world applications. This paper extends current approaches to recommender systems towards a cross-disciplinary perspective by combining the(More)