GroupLens: an open architecture for collaborative filtering of netnews
CSCW '94 Proceedings of the 1994 ACM conference on Computer supported cooperative work
Personalization on the Net using Web mining: introduction
Communications of the ACM
Item-based collaborative filtering recommendation algorithms
Proceedings of the 10th international conference on World Wide Web
Evaluation of Item-Based Top-N Recommendation Algorithms
Proceedings of the tenth international conference on Information and knowledge management
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
Personalization technologies: a process-oriented perspective
Communications of the ACM - The digital society
Introduction to Data Mining, (First Edition)
Introduction to Data Mining, (First Edition)
Intelligent e-government services with personalized recommendation techniques: Research Articles
International Journal of Intelligent Systems
New Recommendation Techniques for Multicriteria Rating Systems
IEEE Intelligent Systems
Designing Specific Weighted Similarity Measures to Improve Collaborative Filtering Systems
ICDM '08 Proceedings of the 8th industrial conference on Advances in Data Mining: Medical Applications, E-Commerce, Marketing, and Theoretical Aspects
UTA-Rec: a recommender system based on multiple criteria analysis
Proceedings of the 2008 ACM conference on Recommender systems
marService: multiattribute utility recommendation for e-markets
International Journal of Computer Applications in Technology
A hybrid recommendation technique based on product category attributes
Expert Systems with Applications: An International Journal
Semantically Enhanced Recommender Systems
OTM '09 Proceedings of the Confederated International Workshops and Posters on On the Move to Meaningful Internet Systems: ADI, CAMS, EI2N, ISDE, IWSSA, MONET, OnToContent, ODIS, ORM, OTM Academy, SWWS, SEMELS, Beyond SAWSDL, and COMBEK 2009
Hybrid web recommender systems
The adaptive web
A Framework of Hybrid Recommendation System for Government-to-Business Personalized E-Services
ITNG '10 Proceedings of the 2010 Seventh International Conference on Information Technology: New Generations
Intelligent techniques for web personalization
ITWP'03 Proceedings of the 2003 international conference on Intelligent Techniques for Web Personalization
A trust-semantic fusion-based recommendation approach for e-business applications
Decision Support Systems
Hybrid recommendation approaches for multi-criteria collaborative filtering
Expert Systems with Applications: An International Journal
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Recommender systems aim to assist web users to find only relevant information to their needs rather than an undifferentiated mass of information. Collaborative filtering (CF) techniques are probably the most popular and widely adopted techniques in recommender systems. Despite of their success in various applications, CF-based techniques still encounter two major limitations, namely sparsity and cold-start problems. More recently, semantic information of items has been successfully used in recommender systems to alleviate such problems. Moreover, the incorporation of multi-criteria ratings in recommender systems can help to produce more accurate recommendations. Thereby, in this paper, we propose a hybrid Multi-Criteria Semantic-enhanced CF (MC-SeCF) approach. The MC-SeCF approach integrates the enhanced MC item-based CF and the item-based semantic filtering approaches to alleviate current limitations of the item-based CF techniques. Experimental results demonstrate the effectiveness of the proposed MC-SeCF approach in terms of improving accuracy, as well as in dealing with very sparse data sets or cold-start items compared to benchmark item-based CF techniques.