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Summary: Personalized Recommendation of TV Programs
L. Ardissono1
, C. Gena1
, P. Torasso1
F. Bellifemine2, A. Chiarotto2, A. Difino2, and B. Negro2
1 Dipartimento di Informatica, Universit`a di Torino, Corso Svizzera 185, Torino, Italy
liliana, cgena, torasso @di.unito.it
2 Telecom Italia Lab, Multimedia Division, via Reiss Romoli 274, Torino, Italy
bellifemine, chiarotto, difino, barbara.negro @tilab.it
Abstract. This paper presents the recommendation techniques applied in Per-
sonal Program Guide (PPG), a system generating personalized Electronic Pro-
gram Guides for digital TV. The PPG recommends TV programs by relying on
the integration of heterogeneous user modeling techniques.
Copyright Springer Verlag. This paper is going to appear in the Proceedings of
the 8th AI*IA Conference, Pisa, 2003, published by Springer Verlag in the Lecture
Notes for Artificial Intelligence collection
(see http://www.springer.de/comp/lncs/index.html).
1 Introduction
The advent of Internet and Word Wide Web makes now available to the users a large
amount of information, products and services. Recommendation techniques [13] based
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