Browsing by Author "Sangüesa i Sole, Ramon"
Now showing items 1-6 of 6
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BayesProfile: application of bayesian networks to website user tracking
Sangüesa i Sole, Ramon; Cortés García, Claudio Ulises; Nicolás, Mario (1998-01)
External research report
Open AccessDetecting the most probable {it next} page a user is bound to visit inside a website has important practical consequences: it allows to suggest recommendations to the visitors as to which may be the pages of interest to ... -
Incremental methods for Bayesian network learning
Roure Alcobé, Josep; Sangüesa i Sole, Ramon (1999-10)
External research report
Open AccessCurrent methods for learning Bayesian Networks are mainly batch methods. That is, they are supposed to act in a single step over the complete set of data. We remark the need to develop new approaches that do not require ... -
Learning causal networks from data
Sangüesa i Sole, Ramon (1996-03)
External research report
Open AccessCausal concepts play a crucial role in many reasoning tasks. Organized as a model revealing the causal structure of a domain, they can guide inference through relevant knowledge. This is a specially difficult knowledge ... -
NetExpert : sistema basado en inteligencia artificial para la localización de expertos
Pujol Serra, Josep M.; Sangüesa i Sole, Ramon (Escola Tècnica Superior d'Enginyers de Telecomunicació de Barcelona, 2001)
Article
Open Access -
Porqpine: a peer-to-peer search engine
Pujol, Josep Maria; Sangüesa i Sole, Ramon; Bermúdez, Juanjo (2003-05)
External research report
Open AccessIn this paper, we present a fully distributed and collaborative search engine for web pages: Porqpine. This system uses a novel query-based model and collaborative filtering techniques in order to obtain user-customize ... -
Probabilistic conditional independence: a similarity-based measure and its application to causal network learning
Sangüesa i Sole, Ramon; Cabós, Joan; Cortés García, Claudio Ulises (1996-06)
External research report
Open AccessA new definition for similarity between possibility distributions is introduced and discussed as a basis for detecting dependence between variables by measuring the similarity degree of their respective distributions. This ...