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AI
2004
Springer

Constraint Satisfaction Methods for Information Personalization

13 years 9 months ago
Constraint Satisfaction Methods for Information Personalization
Constraints formalize the dependencies in a physical world in terms of a logical relation among several unknowns. Constraint satisfaction methods allow efficient navigation of large search spaces to find an optimal solution that satisfies given constraints. This paper explores the application of constraint satisfaction methods to personalize generic information content with respect to a user-model. We present a constraint satisfaction based information personalization framework that (a) generates personalized information via the dynamic selection and synthesis of multiple information-snippets; and (b) ensures that the dynamically adapted personalized information is factually consistent. We present four constraint satisfaction methods that cumulatively work to maximize collaboration and minimize conflicts between a set of information-snippets in order to dynamically generate personalized information.
Syed Sibte Raza Abidi, Yong Han Chong
Added 30 Jun 2010
Updated 30 Jun 2010
Type Conference
Year 2004
Where AI
Authors Syed Sibte Raza Abidi, Yong Han Chong
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