|1/2014 - 18|
TV Recommendation and Personalization Systems: Integrating Broadcast and Video On demand ServicesSOARES, M. , VIANA, P.
|Click to see author's profile in SCOPUS, IEEE Xplore, Web of Science|
|Download PDF (804 KB) | Citation | Downloads: 419 | Views: 2,138|
collaborative filtering, content filtering, recommendation systems, TV-Anytime
recommendation(6), user(5), systems(4)
Blue keywords are present in both the references section and the paper title.
About this article
Date of Publication: 2014-02-28
Volume 14, Issue 1, Year 2014, On page(s): 115 - 120
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2014.01018
Web of Science Accession Number: 000332062300018
SCOPUS ID: 84894614863
The expansion of Digital Television and the convergence between conventional broadcasting and television over IP contributed to the gradual increase of the number of available channels and on demand video content. Moreover, the dissemination of the use of mobile devices like laptops, smartphones and tablets on everyday activities resulted in a shift of the traditional television viewing paradigm from the couch to everywhere, anytime from any device. Although this new scenario enables a great improvement in viewing experiences, it also brings new challenges given the overload of information that the viewer faces. Recommendation systems stand out as a possible solution to help a watcher on the selection of the content that best fits his/her preferences. This paper describes a web based system that helps the user navigating on broadcasted and online television content by implementing recommendations based on collaborative and content based filtering. The algorithms developed estimate the similarity between items and users and predict the rating that a user would assign to a particular item (television program, movie, etc.). To enable interoperability between different systems, programs characteristics (title, genre, actors, etc.) are stored according to the TV-Anytime standard. The set of recommendations produced are presented through a Web Application that allows the user to interact with the system based on the obtained recommendations.
|References|||||Cited By «-- Click to see who has cited this paper|
| G. Adomavicius, Y. Kwon, "New Recommendation Techniques for Multicriteria Rating Systems". IEEE Intelligent Systems, vol. 22, no. 3, pp. 48-55, 2007. |
[CrossRef] [Web of Science Times Cited 145] [SCOPUS Times Cited 232]
 J. Bar-Ilan, K Keenoy, E. Yaari, M. Levene, "User rankings of search results". Journal of the American Society for Information Science and Technology, vol. 58, no. 9, pp. 1254-1266, May 2007.
[CrossRef] [Web of Science Times Cited 26] [SCOPUS Times Cited 40]
 J. Bar-Ilan, M. Mat-Hassan, M. Levene, "Methods for comparing rankings of search engine results". Computer Networks, vol. 50, no. 10, pp. 1448-1463, July 2006.
[CrossRef] [Web of Science Times Cited 50] [SCOPUS Times Cited 78]
 T. Burke, "Hybrid recommender systems: Survey and experiments". Modelling and User-Adapted Interaction, vol. 12 , no. 4, pp. 331-370, November 2002.
[CrossRef] [Web of Science Times Cited 1184] [SCOPUS Times Cited 1850]
 P. Cotter, B. Smith, Barry, "PTV: Intelligent Personalised TV Guides". In: Proceedings of the 12th Innovative Applications of Artificial Intelligence Conference, pp. 957-964, 2000.
 G. Holbling, M. Pleschgatternig, H. Kosch, "PersonalTV - A TV recommendation system using program metadata for content filtering". Multimedia Tools Application, vol. 46, no. 2, pp. 259-288, January 2010.
[CrossRef] [Web of Science Times Cited 3] [SCOPUS Times Cited 7]
 S. H. Hsu, M. H. Wen, H. C. Lin, C. C. Lee, C. H. Lee, "AIMED-A personalized TV Recommendation System". In Proceedings of the Interactive TV: A Shared Experience, 5th European Conference, vol. 4471, pp. 166-174, 2007. Springer Berlin/Heidelberg.
 J. B. Schafer, J. A. Konstan, J. Riedl, "E Recommendation Applications". GroupLens Research Project, Department of Computer Science and Engineering University of Minnesota, 2001.
 S. Velusamy, L. Gopal, S. Bhatnagar, S. Varadarajan, An efficient ad recommendation system for TV programs. Multimedia Systems, vol. 14 no. 2, pp. 73-87, 2008, Springer.
[CrossRef] [Web of Science Times Cited 13] [SCOPUS Times Cited 24]
 X. Su, T. M. Khoshgoftaar, "A Survey of Collaborative Filtering". Journal Advances in Artificial Intelligence archive, January 2009.
 Z. Yu, X. Zhou, Y. Hao, J. Gu, "TV program recommendation for multiple viewers based on user profile merging". User Modeling and User Adapted Interaction, vol. 16, no. 1, pp. 62-82, 2006.
[CrossRef] [Web of Science Times Cited 121] [SCOPUS Times Cited 196]
Web of Science® Citations for all references: 1,542 TCR
SCOPUS® Citations for all references: 2,427 TCR
Web of Science® Average Citations per reference: 129 ACR
SCOPUS® Average Citations per reference: 202 ACR
TCR = Total Citations for References / ACR = Average Citations per Reference
We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more
Citations for references updated on 2018-08-12 06:40 in 55 seconds.
Note1: Web of Science® is a registered trademark of Clarivate Analytics.
Note2: SCOPUS® is a registered trademark of Elsevier B.V.
Disclaimer: All queries to the respective databases were made by using the DOI record of every reference (where available). Due to technical problems beyond our control, the information is not always accurate. Please use the CrossRef link to visit the respective publisher site.
Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
All rights reserved: Advances in Electrical and Computer Engineering is a registered trademark of the Stefan cel Mare University of Suceava. No part of this publication may be reproduced, stored in a retrieval system, photocopied, recorded or archived, without the written permission from the Editor. When authors submit their papers for publication, they agree that the copyright for their article be transferred to the Faculty of Electrical Engineering and Computer Science, Stefan cel Mare University of Suceava, Romania, if and only if the articles are accepted for publication. The copyright covers the exclusive rights to reproduce and distribute the article, including reprints and translations.
Permission for other use: The copyright owner's consent does not extend to copying for general distribution, for promotion, for creating new works, or for resale. Specific written permission must be obtained from the Editor for such copying. Direct linking to files hosted on this website is strictly prohibited.
Disclaimer: Whilst every effort is made by the publishers and editorial board to see that no inaccurate or misleading data, opinions or statements appear in this journal, they wish to make it clear that all information and opinions formulated in the articles, as well as linguistic accuracy, are the sole responsibility of the author.