Computing the SVD of a General Matrix Product/Quotient
SIAM Journal on Matrix Analysis and Applications
Amazon.com Recommendations: Item-to-Item Collaborative Filtering
IEEE Internet Computing
Evaluating collaborative filtering recommender systems
ACM Transactions on Information Systems (TOIS)
Item-based top-N recommendation algorithms
ACM Transactions on Information Systems (TOIS)
Proceedings of the 10th international conference on Intelligent user interfaces
IEEE Transactions on Knowledge and Data Engineering
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
Using SVD and demographic data for the enhancement of generalized Collaborative Filtering
Information Sciences: an International Journal
A new similarity measure for collaborative filtering to alleviate the new user cold-starting problem
Information Sciences: an International Journal
Collaborative recommender systems: Combining effectiveness and efficiency
Expert Systems with Applications: An International Journal
International Journal of Learning Technology
Personalization in an interactive learning environment through a virtual character
Computers & Education
Evaluation of recommender systems: A new approach
Expert Systems with Applications: An International Journal
Introduction to Information Retrieval
Introduction to Information Retrieval
A multi-disciplinar recommender system to advice research resources in University Digital Libraries
Expert Systems with Applications: An International Journal
A hybrid of sequential rules and collaborative filtering for product recommendation
Information Sciences: an International Journal
Selecting a small number of products for effective user profiling in collaborative filtering
Expert Systems with Applications: An International Journal
Score normalization in multimodal biometric systems
Pattern Recognition
Collaborative filtering with ordinal scale-based implicit ratings for mobile music recommendations
Information Sciences: an International Journal
A filtering and recommender system for e-scholars
International Journal of Technology Enhanced Learning
International Journal of Approximate Reasoning
Information Sciences: an International Journal
Workshop on recommender systems for technology enhanced learning
Proceedings of the fourth ACM conference on Recommender systems
Recommender Systems Handbook
Collaborative user modeling with user-generated tags for social recommender systems
Expert Systems with Applications: An International Journal
Information Sciences: an International Journal
Social navigation support in a course recommendation system
AH'06 Proceedings of the 4th international conference on Adaptive Hypermedia and Adaptive Web-Based Systems
A collaborative filtering approach to mitigate the new user cold start problem
Knowledge-Based Systems
Using past-prediction accuracy in recommender systems
Information Sciences: an International Journal
Expert Systems with Applications: An International Journal
Development of an adaptive and intelligent tutoring system by expert system
International Journal of Computer Applications in Technology
Design and evaluation of an adaptive and intelligent tutoring system by expert system
Intelligent Decision Technologies
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To carry out effective teaching/learning processes, lecturers in a variety of educational institutions frequently need support. They therefore resort to advice from more experienced lecturers, to formal training processes such as specializations, master or doctoral degrees, or to self-training. High costs in time and money are invariably involved in the processes of formal training, while self-training and advice each bring their own specific risks (e.g. of following new trends that are not fully evaluated or the risk of applying techniques that are inappropriate in specific contexts).This paper presents a system that allows lecturers to define their best teaching strategies for use in the context of a specific class. The context is defined by: the specific characteristics of the subject being treated, the specific objectives that are expected to be achieved in the classroom session, the profile of the students on the course, the dominant characteristics of the teacher, and the classroom environment for each session, among others. The system presented is the Recommendation System of Pedagogical Patterns (RSPP). To construct the RSPP, an ontology representing the pedagogical patterns and their interaction with the fundamentals of the educational process was defined. A web information system was also defined to record information on courses, students, lecturers, etc.; an option based on a unified hybrid model (for content and collaborative filtering) of recommendations for pedagogical patterns was further added to the system. RSPP features a minable view, a tabular structure that summarizes and organizes the information registered in the rest of the system as well as facilitating the task of recommendation. The data recorded in the minable view is taken to a latent space, where noise is reduced and the essence of the information contained in the structure is distilled. This process makes use of Singular Value Decomposition (SVD), commonly used by information retrieval and recommendation systems. Satisfactory results both in the accuracy of the recommendations and in the use of the general application open the door for further research and expand the role of recommender systems in educational teacher support processes.