Journal ArticleDOI
A hybrid knowledge-based recommender system for e-learning based on ontology and sequential pattern mining
TLDR
The proposed hybrid approach can alleviate both the cold-start and data sparsity problems by making use of ontological domain knowledge and learner’s sequential access pattern respectively before the initial data to work on is available in the recommender system.About:
This article is published in Future Generation Computer Systems.The article was published on 2017-07-01. It has received 195 citations till now. The article focuses on the topics: Recommender system & Domain knowledge.read more
Citations
More filters
Journal ArticleDOI
A recommender system based on collaborative filtering using ontology and dimensionality reduction techniques
TL;DR: This research solves two main drawbacks of recommender systems, sparsity and scalability, using dimensionality reduction and ontology techniques, and uses ontology to improve the accuracy of recommendations in CF part.
Journal ArticleDOI
Review of ontology-based recommender systems in e-learning
Gina George,Anisha M. Lal +1 more
TL;DR: The comprehensive survey in this paper gives an overview of the research in progress using ontology to achieve personalization in recommender systems in the e-learning domain.
Journal ArticleDOI
EARS: Emotion-aware recommender system based on hybrid information fusion
TL;DR: An emotion-aware recommender system based on hybrid information fusion in which three representative types of information are fused to comprehensively analyze the user’s features is proposed.
Journal ArticleDOI
A hybrid recommender system for e-learning based on context awareness and sequential pattern mining
TL;DR: Evaluation of the proposed hybrid recommendation approach combining context awareness, sequential pattern mining (SPM) and CF algorithms for recommending learning resources to the learners indicated that it can outperform other recommendation methods in terms of quality and accuracy of recommendations.
Journal ArticleDOI
A Survey of Recommendation Systems: Recommendation Models, Techniques, and Application Fields
TL;DR: It was found that the flow and quantitative growth of various detailed studies of recommendation systems interact with the business growth of the actual applied service field.
References
More filters
Journal ArticleDOI
Cold-Start Recommendation with Provable Guarantees: A Decoupled Approach
TL;DR: This paper proposes a novel and general algorithmic framework based on matrix completion that simultaneously exploits the similarity information among users and items to alleviate the cold-start problem and is believed to be the first algorithm that addresses theColdstart problem with provable guarantees on performance.
Journal ArticleDOI
An imputation-based matrix factorization method for improving accuracy of collaborative filtering systems
TL;DR: A novel matrix factorization method called IMULT, which utilizes imputed rating to mitigate the sparsity problem, is proposed and results show that IMULT performed better than ALS, SGD, RSGD, SVD++ and MULT.
Journal ArticleDOI
e-Learning recommender system for a group of learners based on the unified learner profile approach
TL;DR: This paper focuses on the problem of recommending resources to a group of learners rather than to an individual and proposes a profile merging scheme for the ULP by utilizing learning styles, knowledge levels and ratings of learners in a group for effective group recommendations.
Journal ArticleDOI
Measuring learner's performance in e-learning recommender systems
TL;DR: A new e-learning recommender system framework is proposed that uses content-based filtering and good learners' ratings to recommend learning materials, and in turn is able to increase the student's performance.
Journal ArticleDOI
A hybrid system of pedagogical pattern recommendations based on singular value decomposition and variable data attributes
Carlos Cobos,Orlando Rodriguez,Jarvein Rivera,John Betancourt,Martha Mendoza,Elizabeth León,Enrique Herrera-Viedma +6 more
TL;DR: The Recommendation System of Pedagogical Patterns (RSPP) as discussed by the authors is a system that allows lecturers to define their best teaching strategies for use in the context of a specific class, 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 a teacher, and the classroom environment for each session.