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PAI is a multidisciplinary research project funded by the National Technology Agency (Tekes) as part of the national research programme on User-Oriented Information Technology (USIX) to take place in 2000-2002.
The main objective of the PAI project is to develope methods for applying probabilistic modeling techniques, such as Bayesian network models, in building and using personalized, adaptive user interfaces. Specific research problems include user data segmentation, user profiling and user identification, and location-aware computing. The associated pilot-projects focus on problems related to intelligent educational technologies (EDUTECH), adaptive WWW services and adaptive mobile services.
In user data segmentation the goal of the project is to develop computationally efficient methods for partitioning the available data into meaningful clusters by using adaptive Bayesian network modeling techniques. In user profiling these clusters are used for producing a semantic interpretation of the domain as a set of probabilistic user profiles. These profiles can be studied by using various data mining and visualization techniques, and the results of this type of an analysis can be used off-line in designing personalized interfaces for WWW services or educational media. In user identification the produced probabilistic model is used for on-line identification of the user profile from partial and uncertain observations. This type of methods can be used for developing adaptive interfaces. In the area of location-aware computing, the project focuses on studying how the adaptive probabilistic modeling techniques can be used in estimating the location of a mobile user, based on the measurements provided by the mobile terminal.
Henry Tirri
University of Helsinki
Department of Computer Science
P.O.Box 26, 00014 University of Helsinki, Finland
Tel: +358 9 191 44173
Mobile: +358 40 5000 533
Fax: +358 9 191 44441
Email: Henry.Tirri@cs.Helsinki.FI