User Modeling and Recommendation Techniques for Personalized Electronic Program Guides

This chapter presents the recommendation techniques applied in Personal Program Guide (PPG). This is a system generating personalized Electronic Program Guides for Digital TV. The PPG manages a user model that stores the estimates of the individual user’s preferences for TV program categories. This model results from the integration of different preference acquisition modules that handle explicit user preferences, stereotypical information about TV viewers, and information about the user’s viewing behavior. The observation of the individual viewing behavior is particularly easy because the PPG runs on the set-top box and is deeply integrated with the TV playing and the video recording services offered by that type of device.

[1]  Alfred Kobsa,et al.  User Models in Dialog Systems , 1989, Symbolic Computation.

[2]  John Riedl,et al.  Combining Collaborative Filtering with Personal Agents for Better Recommendations , 1999, AAAI/IAAI.

[3]  Richard Riecken,et al.  Growth in personalization and business , 2000, CACM.

[4]  John Zimmerman,et al.  TV Personalization System , 2004, Personalized Digital Television.

[5]  Paul Resnick,et al.  Recommender systems , 1997, CACM.

[6]  Richard E. Neapolitan,et al.  Probabilistic reasoning in expert systems - theory and algorithms , 2012 .

[7]  Liliana Ardissono,et al.  Architecture of a system for the generation of personalized Electronic Program Guides , 2001 .

[8]  DIMITRIOS PIERRAKOS,et al.  User Modeling and User-Adapted Interaction , 1994, User Modeling and User-Adapted Interaction.

[9]  Liliana Ardissono,et al.  Personalized Recommendation of TV Programs , 2003, AI*IA.

[10]  Judith Masthoff,et al.  Group Modeling: Selecting a Sequence of Television Items to Suit a Group of Viewers , 2004, User Modeling and User-Adapted Interaction.

[11]  Zina M. Ibrahim,et al.  Advances in Artificial Intelligence , 2003, Lecture Notes in Computer Science.

[12]  Robin D. Burke,et al.  Hybrid Recommender Systems: Survey and Experiments , 2002, User Modeling and User-Adapted Interaction.

[13]  Javed Mostafa Guest Editor's Introduction: Information Customization , 2002, IEEE Intell. Syst..

[14]  Liliana Ardissono,et al.  Tailoring the Interaction with Users in Web Stores , 2000, User Modeling and User-Adapted Interaction.

[15]  U. Reimers,et al.  Digital video broadcasting , 1998, IEEE Commun. Mag..

[16]  Patrick Baudisch,et al.  TV Scout: Lowering the Entry Barrier to Personalized TV Program Recommendation , 2002, From Integrated Publication and Information Systems to Virtual Information and Knowledge Environments.

[17]  J. van Leeuwen,et al.  Adaptive Hypermedia and Adaptive Web-Based Systems , 2002, Lecture Notes in Computer Science.

[18]  Gobinda G. Chowdhury,et al.  Introduction to Modern Information Retrieval , 1999 .

[19]  Yumiko Hara,et al.  Categorization of Japanese TV Viewers Based on Program Genres They Watch , 2004, User Modeling and User-Adapted Interaction.

[20]  Cristina Gena,et al.  Designing TV Viewer Stereotypes for an Electronic Program Guide , 2001, User Modeling.

[21]  M. Ceccarelli,et al.  A PERSONAL TV RECEIVER WITH STORAGE AND RETRIEVAL CAPABILITIES , 2001 .

[22]  Elaine Rich,et al.  Stereotypes and User Modeling , 1989 .

[23]  Barry Smyth,et al.  A personalized television listings service , 2000, CACM.

[24]  Jeroen Van Barneveld,et al.  Designing Usable Interfaces for TV Recommender Systems , 2004, Personalized Digital Television.

[25]  Matthew C. Valenti,et al.  Digital Video Broadcasting , 2004 .