Adaptive Learning of Probabilistic Graphical Models in Data Mining and Automatic Personalisation TIN2004-06204-C03

In this project we intend to develop the methodology of adaptive learning of probabilistic graphical models, specially Bayesian networks, focused on its application to data mining and automatic personalisation. The background software is the Elvira platform [22], in which development the groups in this project took part, through projects TIC971137-C04 and TIC2001-2973-C05. The most important part of the project is devoted to the development of applications, highly based on the Elvira platform. Each sub-project is responsible of two applications. Sub-project 1 (Almeŕıa) is developing a personalised academic advisor for students, based on the construction of a Bayesian network from the student database of the University of Almeŕıa. Also, it has implemented an application for bookmarks personalisation in web browsers. Sub-project 2 (Albacete) works in the implementation of an advisor for academic managers based on a Bayesian network obtained from the data provided by the University of Almeŕıa. Furthermore, it is developing a system for the classification of e-mail into folders. Sub-project 3 (Granada) is the responsible of the implementation of a system for personalising the result of a web search based on the user’s preferences. Also, it works in the construction of a system for detecting urgent e-mail, specially useful when only a reduced number of messages can be read.