Analysis of recommendation algorithms for e-commerce
Proceedings of the 2nd ACM conference on Electronic commerce
Formal Concept Analysis: Mathematical Foundations
Formal Concept Analysis: Mathematical Foundations
Methods and metrics for cold-start recommendations
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
Latent semantic models for collaborative filtering
ACM Transactions on Information Systems (TOIS)
Trust-aware recommender systems
Proceedings of the 2007 ACM conference on Recommender systems
Using error-correcting dependencies for collaborative filtering
Data & Knowledge Engineering
Learning preferences of new users in recommender systems: an information theoretic approach
ACM SIGKDD Explorations Newsletter
A hybrid recommendation technique based on product category attributes
Expert Systems with Applications: An International Journal
A Research on Fuzzy Formal Concept Analysis Based Collaborative Filtering Recommendation System
KAM '09 Proceedings of the 2009 Second International Symposium on Knowledge Acquisition and Modeling - Volume 03
New fast algorithm for constructing concept lattice
ICCSA'07 Proceedings of the 2007 international conference on Computational science and Its applications - Volume Part II
RSS-based e-learning recommendations exploiting fuzzy FCA for Knowledge Modeling
Applied Soft Computing
Hierarchical web resources retrieval by exploiting Fuzzy Formal Concept Analysis
Information Processing and Management: an International Journal
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Recommender systems rely on the opinions of a community of users to provide "recommendations" that can help users of the same community in discerning content of interest from a wide range of possibilities. Particularly, collaborative information filtering represents one of techniques widely exploited by recommender systems to suggest which items better meet the user needs and preferences. This paper introduces a model for collaborative filtering based on Formal Concept Analysis, a theoretical framework suitable to generate correlations among data through a lattice design. In particular, a fuzzy annotation of the lattice allows discovering similarities among items as well as users, arranged as a ranked list.