GroupLens: an open architecture for collaborative filtering of netnews
CSCW '94 Proceedings of the 1994 ACM conference on Computer supported cooperative work
The personal electronic program guide—towards the pre-selection of individual TV programs
CIKM '96 Proceedings of the fifth international conference on Information and knowledge management
Fab: content-based, collaborative recommendation
Communications of the ACM
Recommendation as classification: using social and content-based information in recommendation
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
An algorithmic framework for performing collaborative filtering
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
A personalized television listings service
Communications of the ACM
Explaining collaborative filtering recommendations
CSCW '00 Proceedings of the 2000 ACM conference on Computer supported cooperative work
Item-based collaborative filtering recommendation algorithms
Proceedings of the 10th international conference on World Wide Web
Hybrid Recommender Systems: Survey and Experiments
User Modeling and User-Adapted Interaction
Eigentaste: A Constant Time Collaborative Filtering Algorithm
Information Retrieval
Document Ranking and the Vector-Space Model
IEEE Software
TV Scout: Lowering the Entry Barrier to Personalized TV Program Recommendation
AH '02 Proceedings of the Second International Conference on Adaptive Hypermedia and Adaptive Web-Based Systems
The Development and Prospect of Personalized TV Program Recommendation Systems
MSE '02 Proceedings of the Fourth IEEE International Symposium on Multimedia Software Engineering
Intelligent Media Agents in Interactive Television Systems
ICMCS '95 Proceedings of the International Conference on Multimedia Computing and Systems
Evaluating collaborative filtering recommender systems
ACM Transactions on Information Systems (TOIS)
A collaborative filtering algorithm and evaluation metric that accurately model the user experience
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Incorporating contextual information in recommender systems using a multidimensional approach
ACM Transactions on Information Systems (TOIS)
Improving recommendation lists through topic diversification
WWW '05 Proceedings of the 14th international conference on World Wide Web
IEEE Transactions on Knowledge and Data Engineering
Applying SVD on Item-based Filtering
ISDA '05 Proceedings of the 5th International Conference on Intelligent Systems Design and Applications
Improving the prediction accuracy of recommendation algorithms: Approaches anchored on human factors
Interacting with Computers
Using SVD and demographic data for the enhancement of generalized Collaborative Filtering
Information Sciences: an International Journal
Multimedia Tools and Applications
Collaborative recommender systems: Combining effectiveness and efficiency
Expert Systems with Applications: An International Journal
PeerChooser: visual interactive recommendation
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
What Can I Watch on TV Tonight?
AH '08 Proceedings of the 5th international conference on Adaptive Hypermedia and Adaptive Web-Based Systems
The measurement of user satisfaction with question answering systems
Information and Management
Information Sciences: an International Journal
Improving memory-based collaborative filtering via similarity updating and prediction modulation
Information Sciences: an International Journal
AIMED: a personalized TV recommendation system
EuroITV'07 Proceedings of the 5th European conference on Interactive TV: a shared experience
Data mining for web personalization
The adaptive web
Collaborative filtering recommender systems
The adaptive web
Content-based recommendation systems
The adaptive web
Social comparisons to motivate contributions to an online community
PERSUASIVE'07 Proceedings of the 2nd international conference on Persuasive technology
Empirical analysis of predictive algorithms for collaborative filtering
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
What's on TV tonight? An efficient and effective personalized recommender system of TV programs
IEEE Transactions on Consumer Electronics
Information Sciences: an International Journal
Personalized recommendation of popular blog articles for mobile applications
Information Sciences: an International Journal
Information Sciences: an International Journal
Collaborative filtering based on significances
Information Sciences: an International Journal
Preference elicitation techniques for group recommender systems
Information Sciences: an International Journal
Expert Systems with Applications: An International Journal
Personalised placement in networked video
Proceedings of the 21st international conference companion on World Wide Web
A slope one collaborative filtering recommendation algorithm using uncertain neighbors optimizing
WAIM'11 Proceedings of the 2011 international conference on Web-Age Information Management
An adaptive approach to dealing with unstable behaviour of users in collaborative filtering systems
Journal of Information Science
Incorporating reliability measurements into the predictions of a recommender system
Information Sciences: an International Journal
On-line dynamic adaptation of fuzzy preferences
Information Sciences: an International Journal
A group recommendation approach for service selection
Proceedings of the Fourth Asia-Pacific Symposium on Internetware
Information Processing and Management: an International Journal
Trees for explaining recommendations made through collaborative filtering
Information Sciences: an International Journal
Novel personal and group-based trust models in collaborative filtering for document recommendation
Information Sciences: an International Journal
Improving collaborative filtering-based recommender systems results using Pareto dominance
Information Sciences: an International Journal
Knowledge-Based Systems
Self-configuring data mining for ubiquitous computing
Information Sciences: an International Journal
TV predictor: personalized program recommendations to be displayed on SmartTVs
Proceedings of the 2nd International Workshop on Big Data, Streams and Heterogeneous Source Mining: Algorithms, Systems, Programming Models and Applications
Towards a journalist-based news recommendation system: The Wesomender approach
Expert Systems with Applications: An International Journal
Collaborative filtering with social regularization for TV program recommendation
Knowledge-Based Systems
Intelligent patent recommendation system for innovative design collaboration
Journal of Network and Computer Applications
A quality based recommender system to disseminate information in a university digital library
Information Sciences: an International Journal
QA document recommendations for communities of question-answering websites
Knowledge-Based Systems
Hybrid recommendation approaches for multi-criteria collaborative filtering
Expert Systems with Applications: An International Journal
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With the advent of new cable and satellite services, and the next generation of digital TV systems, people are faced with an unprecedented level of program choice. This often means that viewers receive much more information than they can actually manage, which may lead them to believe that they are missing programs that could likely interest them. In this context, TV program recommendation systems allow us to cope with this problem by automatically matching user's likes to TV programs and recommending the ones with higher user preference. This paper describes the design, development, and startup of queveo.tv: a Web 2.0 TV program recommendation system. The proposed hybrid approach (which combines content-filtering techniques with those based on collaborative filtering) also provides all typical advantages of any social network, such as supporting communication among users as well as allowing users to add and tag contents, rate and comment the items, etc. To eliminate the most serious limitations of collaborative filtering, we have resorted to a well-known matrix factorization technique in the implementation of the item-based collaborative filtering algorithm, which has shown a good behavior in the TV domain. Every step in the development of this application was taken keeping always in mind the main goal: to simplify as much as possible the user task of selecting what program to watch on TV.