Intelligent Systems for Tourism
IEEE Intelligent Systems
Amazon.com Recommendations: Item-to-Item Collaborative Filtering
IEEE Internet Computing
Fuzzy logic methods in recommender systems
Fuzzy Sets and Systems - Theme: Multicriteria decision
Architectures Supporting e-Learning through Collaborative Virtual Environments: The Case of INVITE
ICALT '01 Proceedings of the IEEE International Conference on Advanced Learning Technologies
Evaluating collaborative filtering recommender systems
ACM Transactions on Information Systems (TOIS)
PocketLens: Toward a personal recommender system
ACM Transactions on Information Systems (TOIS)
An Online Recommender System for Large Web Sites
WI '04 Proceedings of the 2004 IEEE/WIC/ACM International Conference on Web Intelligence
IEEE Transactions on Knowledge and Data Engineering
Service-Oriented Grid Architecture and Middleware Technologies for Collaborative E-Learning
SCC '05 Proceedings of the 2005 IEEE International Conference on Services Computing - Volume 02
An Improvement to Collaborative Filtering for Recommender Systems
CIMCA '05 Proceedings of the International Conference on Computational Intelligence for Modelling, Control and Automation and International Conference on Intelligent Agents, Web Technologies and Internet Commerce Vol-1 (CIMCA-IAWTIC'06) - Volume 01
CinemaScreen Recommender Agent: Combining Collaborative and Content-Based Filtering
IEEE Intelligent Systems
Improving Accuracy of Recommender System by Clustering Items Based on Stability of User Similarity
CIMCA '06 Proceedings of the International Conference on Computational Inteligence for Modelling Control and Automation and International Conference on Intelligent Agents Web Technologies and International Commerce
Improving the prediction accuracy of recommendation algorithms: Approaches anchored on human factors
Interacting with Computers
Collaborative recommender systems: Combining effectiveness and efficiency
Expert Systems with Applications: An International Journal
Empirical analysis of predictive algorithms for collaborative filtering
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Location-based recommendation system using Bayesian user's preference model in mobile devices
UIC'07 Proceedings of the 4th international conference on Ubiquitous Intelligence and Computing
A new collaborative filtering metric that improves the behavior of recommender systems
Knowledge-Based Systems
e-learning experience using recommender systems
Proceedings of the 42nd ACM technical symposium on Computer science education
Expert Systems with Applications: An International Journal
Collaborative filtering based on significances
Information Sciences: an International Journal
Extended precision quality measure for recommender systems
CAEPIA'11 Proceedings of the 14th international conference on Advances in artificial intelligence: spanish association for artificial intelligence
A collaborative filtering approach to mitigate the new user cold start problem
Knowledge-Based Systems
Incremental Collaborative Filtering recommender based on Regularized Matrix Factorization
Knowledge-Based Systems
Top-N news recommendations in digital newspapers
Knowledge-Based Systems
A careful assessment of recommendation algorithms related to dimension reduction techniques
Knowledge-Based Systems
Interest-based real-time content recommendation in online social communities
Knowledge-Based Systems
A collaborative filtering similarity measure based on singularities
Information Processing and Management: an International Journal
A literature review and classification of recommender systems research
Expert Systems with Applications: An International Journal
User satisfaction in long term group recommendations
ICCBR'11 Proceedings of the 19th international conference on Case-Based Reasoning Research and Development
Using personality to create alliances in group recommender systems
ICCBR'11 Proceedings of the 19th international conference on Case-Based Reasoning Research and Development
Using past-prediction accuracy in recommender systems
Information Sciences: an International Journal
Identifying patterns in learner's behavior Using Markov chains and n-gram models
CSCC'11 Proceedings of the 2nd international conference on Circuits, Systems, Communications & Computers
A framework for collaborative filtering recommender systems
Expert Systems with Applications: An International Journal
Multi-context recommendation in technology enhanced learning
ITS'12 Proceedings of the 11th international conference on Intelligent Tutoring Systems
RESYGEN: A Recommendation System Generator using domain-based heuristics
Expert Systems with Applications: An International Journal
A balanced memory-based collaborative filtering similarity measure
International Journal of Intelligent Systems
Social factors in group recommender systems
ACM Transactions on Intelligent Systems and Technology (TIST) - Special section on twitter and microblogging services, social recommender systems, and CAMRa2010: Movie recommendation in context
Improving collaborative filtering-based recommender systems results using Pareto dominance
Information Sciences: an International Journal
Knowledge-Based Systems
Boosting the K-Nearest-Neighborhood based incremental collaborative filtering
Knowledge-Based Systems
Including social factors in an argumentative model for Group Decision Support Systems
Decision Support Systems
Hierarchical graph maps for visualization of collaborative recommender systems
Journal of Information Science
Hybrid recommendation approaches for multi-criteria collaborative filtering
Expert Systems with Applications: An International Journal
Clustering-based diversity improvement in top-N recommendation
Journal of Intelligent Information Systems
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In the context of e-learning recommender systems, we propose that the users with greater knowledge (for example, those who have obtained better results in various tests) have greater weight in the calculation of the recommendations than the users with less knowledge. To achieve this objective, we have designed some new equations in the nucleus of the memory-based collaborative filtering, in such a way that the existent equations are extended to collect and process the information relative to the scores obtained by each user in a variable number of level tests.