Fuzzy sets, uncertainty, and information
Fuzzy sets, uncertainty, and information
Fuzzy set theory—and its applications (3rd ed.)
Fuzzy set theory—and its applications (3rd ed.)
Comparing feature-based and clique-based user models for movie selection
Proceedings of the third ACM conference on Digital libraries
Recommendation as classification: using social and content-based information in recommendation
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Analysis of recommendation algorithms for e-commerce
Proceedings of the 2nd ACM conference on Electronic commerce
On the possibilistic decision model: from decision under uncertainty to case-based decision
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems - A special issue on fuzzy measures
Similarity and compatibility in fuzzy set theory: assessment and applications
Similarity and compatibility in fuzzy set theory: assessment and applications
Fuzzy Sets and Systems: Theory and Applications
Fuzzy Sets and Systems: Theory and Applications
Hybrid Recommender Systems: Survey and Experiments
User Modeling and User-Adapted Interaction
E-Commerce Recommendation Applications
Data Mining and Knowledge Discovery
Targeted E-commerce Marketing Using Fuzzy Intelligent Agents
IEEE Intelligent Systems
Flexibility and fuzzy case-based evaluation in querying: an illustration in an experimental setting
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Considerations for using fuzzy set theory and probability theory
Fuzzy logic and probability applications
Fuzzy logic methods in recommender systems
Fuzzy Sets and Systems - Theme: Multicriteria decision
Evaluating collaborative filtering recommender systems
ACM Transactions on Information Systems (TOIS)
Item-based top-N recommendation algorithms
ACM Transactions on Information Systems (TOIS)
Personalized Product Recommendation in e-Commerce
EEE '04 Proceedings of the 2004 IEEE International Conference on e-Technology, e-Commerce and e-Service (EEE'04)
A collaborative filtering algorithm and evaluation metric that accurately model the user experience
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
IEEE Transactions on Knowledge and Data Engineering
Fuzzy methods for case-based recommendation and decision support
Journal of Intelligent Information Systems
Risk-based access control systems built on fuzzy inferences
ASIACCS '10 Proceedings of the 5th ACM Symposium on Information, Computer and Communications Security
Mamdani fuzzy logic controller with mobile agents for matching
NN'10/EC'10/FS'10 Proceedings of the 11th WSEAS international conference on nural networks and 11th WSEAS international conference on evolutionary computing and 11th WSEAS international conference on Fuzzy systems
User preferences discovery using fuzzy models
Fuzzy Sets and Systems
Sem-Fit: A semantic based expert system to provide recommendations in the tourism domain
Expert Systems with Applications: An International Journal
Evaluation and recommendation methods based on graph model
BI'11 Proceedings of the 2011 international conference on Brain informatics
Information Sciences: an International Journal
Supervised Pseudo Self-Evolving Cerebellar algorithm for generating fuzzy membership functions
Expert Systems with Applications: An International Journal
Electronic Commerce Research and Applications
A design of knowledge management tool for supporting product development
Information Processing and Management: an International Journal
Folksonomy-based fuzzy user profiling for improved recommendations
Expert Systems with Applications: An International Journal
A quality based recommender system to disseminate information in a university digital library
Information Sciences: an International Journal
Hybrid recommendation approaches for multi-criteria collaborative filtering
Expert Systems with Applications: An International Journal
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Representation of features of items and user feedback, and reasoning about their relationships are major problems in recommender systems. This is because item features and user feedback are subjective, imprecise and vague. The paper presents a fuzzy set theoretic method (FTM) for recommender systems that handles the non-stochastic uncertainty induced from subjectivity, vagueness and imprecision in the data, and the domain knowledge and the task under consideration. The research further advances the application of fuzzy modeling for content-based recommender systems initially presented by Ronald Yager. The paper defines a representation method, similarity measures and aggregation methods as well as empirically evaluates the methods' performance through simulation using a benchmark movie data. FTM consist of a representation method for items' features and user feedback using fuzzy sets, and a content-based algorithm based on various fuzzy set theoretic similarity measures (the fuzzy set extensions of the Jaccard index, cosine, proximity or correlation similarity measures), and aggregation methods for computing recommendation confidence scores (the maximum-minimum or Weighted-sum fuzzy set theoretic aggregation methods). Compared to the baseline crisp set based method (CSM) presented, the empirical evaluation of the FTM using the movie data and simulation shows an improvement in precision without loss of recall. Moreover, the paper provides a guideline for recommender systems designers that will help in choosing from a combination of one of the fuzzy set theoretic aggregation methods and similarity measures.