An MHP framework to provide intelligent personalized recommendations about digital TV contents

Software - Practice and Experience

Volumn 38, Issue 9, 2008, Pages 925-960

  Bianco Fernández, Yolanda ^a,c   Pazos Arias, José J ^a   Gil Solla, Alberto ^a   Ramos Cabrer, Manuel ^a   López Nores, Martín ^a   García Duque, Jorge ^a   Fernández Vilas, Ana ^a   Díaz Redondo, Rebeca P ^a   Bermejo Muñoz, Jesús ^b  

^a UNIVERSITY OF VIGO   (Spain)

^b Telvent   (Spain)

^c Campus Universitario de Vigo   (Spain)

Author keywords

Automatic content recommenders; Digital TV; MHP; Semantic Web

Indexed keywords

DIGITAL ARITHMETIC; DIGITAL TELEVISION; INFORMATION THEORY; MULTI AGENT SYSTEMS; SEMANTIC WEB; SEMANTICS; STANDARDS; TELEVISION BROADCASTING;

AUDIO-VISUAL CONTENTS; AUTOMATIC CONTENT; DIGITAL TV; END USERS; EXPERIMENTAL EVALUATIONS; MULTIMEDIA HOME PLATFORM (MHP); NEW APPROACHES; SEMANTIC REASONING; SEMANTIC WEB TECHNOLOGIES; TV ANYTIME;

MOBILE TELECOMMUNICATION SYSTEMS;

EID: 47749141158     PISSN: 00380644     EISSN: 1097024X     Source Type: Journal    
DOI: 10.1002/spe.855     Document Type: Article

References (40)

1. Sciadas G. Unveiling the digital divide. Technical Report Connectedness Series 56F0004MIE, No. 7, Statistics Canada: Science, Innovation and Electronic Information Division, 2002.
2. Rast R. The dawn of Digital TV. IEEE Spectrum 2005; 42(10):26-31.
3. Antoniou G, van Harmelen F. A Semantic Web Primer. MIT Press: Cambridge, MA, 2004.
4. Digital Video Broadcasting Consortium. The Multimedia Home Platform specification. ETSI standard TS 102 812 vl. 2.1, 2003.
5. TV-Anytime Forum. Broadcast and on-line services: Search, select, and rightful use of content on personal storage systems. European Standard ETSI TS 102 822 series, 2006.
6. TV-Anytime on DVB. Carriage and signalling of TV-Anytime information in DVB transport streams. European Standard ETSI TS 102 323 V1.2.1, 2006.
7. Kornfeld M, Reimers U. DVB-H, the emerging standard for mobile data communication. EBU Technical Review, 2005.
8. Telia Sonera. MBMS White Paper (2004, August). http://www.medialab.sonera.fi/workspace/MBMSWhitePaper.pdf [16 June 2005].
9. Burke R. Hybrid recommender systems: Survey and experiments. User Modeling and User-Adapted Interaction 2002; 12(4):331-370.
10. Das D, ter Horst H. Recommender systems for TV. Recommender Systems: Papers from the AAAI Workshop. Technical Report WS-98-08. American Association for Artificial Intelligence, 2001; 151-160.
11. Zimmerman J, Kurapati K, Buczak A, Schafer D, Gutta S, Martino J. TV personalization system: Design of a TV show recommender engine and Interface. Personalized Digital Television: Targeting Programs to Individual Viewers. Kluwer Academic Publishers: Dordrecht, 2004; 27-51.
12. Ardissono L, Gena C, Torasso P, Bellifemine F, Difino A, Negro B. User modeling and recommendation techniques for personalized electronic program guides. Personalized Digital Television: Targeting Programs to Individual Viewers. Kluwer Academic Publishers: Dordrecht, 2004; 3-26.
13. Adomavicius G, Tuzhilin A. Towards the next generation of recommender systems: A survey of the state-of-the-art and possible extensions. IEEE Transactions on Knowledge and Data Engineering 2005; 17(6):739-749.
14. Hill W, Stead L, Rosenstein M, Furnas G. Recommending and evaluating choices in a virtual community of use. Proceedings of International Conference on Human Factors in Computing Systems (CHI-95), Vancouver, Canada, 1995; 194-201.
15. Miller B, Albert I, Lam S, Konstan J, Riedl J. Movielens unplugged: Experiences with an occasionally connected recommender system. ACM Conference on Intelligent User Interfaces (1UI-03), Miami, FL, 2003; 263-266.
16. Baudisch P, Bruekner L. TV Scout: Guiding users from printed TV program guides to personalized TV recommendation. Proceedings of the 1st Workshop on Personalization in Future TV (TV-01), Sonthofen, Germany, 2001; 151-160.
17. Schafer JB, Konstan J, Riedl J. Recommender systems in e-commerce. Proceedings of the 1st ACM Conference on Electronic commerce (EC-99), Denver, U.S.A., 1999; 158-166.
18. O'Sullivan D, Smyth B, Wilson D, McDonald K. Improving the quality of the personalized electronic program guide. User Modeling and User-Adapted Interaction 2004; 14:5-36.
19. Ali K, van Stam W. TiVo: Making show recommendations using a distributed collaborative filtering architecture. Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-04), Seattle, U.S.A., 2004; 394-401.
20. Basu C, Hirsh H, Cohen W. Recommendation as classification: Using social and content-based information in recommendation. Proceedings of the 15th National Conference on Artificial Intelligence (AAAI-98), Madison, WI, 1998; 714-720.
21. McGuinness D, van Harmelen F. OWL Web Ontology Language Overview. W3C Recommendation, 2004.
22. Middleton S. Capturing knowledge of user preferences with recommender systems. PhD Thesis, Department of Electronic and Computer Science. University of Southampton, 2003.
23. Blanco-Fernández Y, Pazos-Arias J, Gil-Solla A, Ramos-Cabrer M. AVATAR: A flexible approach to improve the personalized TV by semantic inference. Proceedings of Workshop on Web Personalization, Recommender Systems and Intelligent User Interfaces (WPRSIUI-05), Reading, U.K., 2005; 69-79.
24. Clark J. XSLT: extensible Stylesheet Language Transformations. W3C Recommendation, 1999.
25. Dimitrova N, Zimmerman J, Janevski A, Agnihotri L, Haas N, Bolle R. Content augmentation aspects of personalized entertainment experience. Proceedings of the 3rd Workshop on Personalization in Future TV (TV-03), Johnstown, U.S.A., 2003; 42-51.
26. Prata A, Guimaraes N, Kommers P. iTV enhanced systems for generating multi-device personalized online learning environments. Proceedings of the 4th Workshop on Personalization in Future TV (TV-04), Eindhoven, The Netherlands, 2004; 274-280.
27. Mobasher B, Jin X, Zhou Y. Semantically enhanced collaborative filtering on the Web. Web Mining: Applications and Techniques. IDEA Group Publishing: New York, U.S.A., 2004; 57-76.
28. Hobbs JR, Pan F. An ontology of time for the Semantic Web. ACM Transactions on Asian Language Processing (TALIP): Special Issue on Temporal Information Processing 2004; 3(l):66-85.
29. Bianco-Fernández Y, Pazos-Arias J, Gil-Solla A, Ramos-Cabrer M, López-Nores M, Barragáns-Martínez B. AVATAR: Modeling users by dynamic ontologies in a TV recommender system based on semantic reasoning. Proceedings of the 3rd European Conference on Interactive Television (EuroITV-05), Aalborg, Denmark, 2005; 173-183.
30. Ziegler C, Schmidt-Thieme L, Lausen G. Exploiting semantic product descriptions for recommender systems. Proceedings of the 2nd ACM SIGIR Semantic Web and Information Retrieval Workshop (SWIR-04), Sheffield, U.K., 2004; 22-32.
31. Ganesan P, Garcia-Molina H, Widom J. Exploiting hierarchical domain structure to compute similarity. ACM Transactions on Information Systems 2003; 21(l):64-93.
32. Resnik P. Semantic similarity in a taxonomy: An information-based measure and its application to problems of ambiguity in natural language. Journal of Artificial Intelligence Research 1999; 11(l):95-130.
33. Lin D. An information-theoretic definition of similarity. Proceedings of 15th International Conference on Machine Learning (ICML-98), Madison, WI, 1998; 296-304.
34. Pazzani M. A framework for collaborative, content-based and demographic Filtering. Artificial Intelligence Review 1999; 13(5):393-408.
35. Melville P, Mooney RJ, Nagarajan R. Content-boosted collaborative filtering for improved recommendations. Proceedings of 18th National Conference on Artificial Intelligence, Edmonton, Alberta, Canada, 2002; 187-192.
36. Berry MW, Dumais ST, Brien GWO. Using linear algebra for intelligent information retrieval. SIAM Review 1994; 37(l):573-595.
37. Pazos-Arias JJ, Lóapez-Nores M, García-Duque J, Gil-Solla A, Ramos-Cabrer M, Blanco-Fernández Y, Díaz-Redondo RP, Fernández-Vilas A. ATLAS: A framework to provide multiuser and distributed t-learning services over MHP. Software - Practice and Experience 2006; 36(8):845-869.
38. Pazos-Arias JJ, López-Nores M, García-Duque J, Díaz-Redondo RP, Blanco-Fernández Y, Ramos-Cabrer M, Gil-Solla A, Fernández-Vilas A. Provision of distance learning services over Interactive Digital TV with MHP. Computers and Education, Doi: 10.1016/j.compedu.2006.09.008.
39. Napoli P. Audience Economics: Media Institutions and the Audience Marketplace. Columbia University Press: New York, 2003.
40. Webster JG, Phalen PF, Lichty LW. Rating Analysis: The Theory and Practice of Audience Research. Lawrence Erlbaum: London, 2000.