article

Fuzzy logic methods in recommender systems

Author:

Ronald R. YagerAuthors Info & Claims

Fuzzy Sets and Systems, Volume 136, Issue 2

Pages 133 - 149

https://doi.org/10.1016/S0165-0114(02)00223-3

Published: 01 June 2003 Publication History

Abstract

Here we consider methodologies for constructing recommender systems. The approaches studied here differ from collaborative filtering, they are based solely on the preferences of the single individual for whom we are providing the recommendation and make no use of the preferences of other collaborators. We have called these reclusive methods. Another important feature distinguishing these reclusive methods from collaborative methods is that they require a representation of the objects. Considerable use is made of fuzzy set methods for the representation and subsequent construction of justifications and recommendation rules. It is pointed out these reclusive methods rather than being competitive with collaborative methods are complementary.

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Cited By

Lu JMa GZhang G(2024)Fuzzy Machine Learning: A Comprehensive Framework and Systematic ReviewIEEE Transactions on Fuzzy Systems10.1109/TFUZZ.2024.338742932:7(3861-3878)Online publication date: 1-Jul-2024
https://dl.acm.org/doi/10.1109/TFUZZ.2024.3387429
Sha LShao YLi Y(2024)A framework of fermatean fuzzy cognitive map and its extension based on Hamacher operationEngineering Applications of Artificial Intelligence10.1016/j.engappai.2024.108676136:PAOnline publication date: 1-Oct-2024
https://dl.acm.org/doi/10.1016/j.engappai.2024.108676
Sreepada RPatra B(2022)Mitigating long tail effect in recommendations using few shot learning techniqueExpert Systems with Applications: An International Journal10.1016/j.eswa.2019.112887140:COnline publication date: 21-Apr-2022
https://dl.acm.org/doi/10.1016/j.eswa.2019.112887
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Index Terms

Fuzzy logic methods in recommender systems
1. Computing methodologies
  1. Artificial intelligence
    1. Knowledge representation and reasoning
      1. Probabilistic reasoning
      2. Vagueness and fuzzy logic
    2. Natural language processing
2. Theory of computation
  1. Logic
    1. Programming logic
  2. Semantics and reasoning
    1. Program reasoning

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Information & Contributors

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Published In

cover image Fuzzy Sets and Systems

Fuzzy Sets and Systems Volume 136, Issue 2

Theme: Multicriteria decision

June 1, 2003

125 pages

ISSN:0165-0114

Issue’s Table of Contents

Publisher

Elsevier North-Holland, Inc.

United States

Publication History

Published: 01 June 2003

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Cited By

Lu JMa GZhang G(2024)Fuzzy Machine Learning: A Comprehensive Framework and Systematic ReviewIEEE Transactions on Fuzzy Systems10.1109/TFUZZ.2024.338742932:7(3861-3878)Online publication date: 1-Jul-2024
https://dl.acm.org/doi/10.1109/TFUZZ.2024.3387429
Sha LShao YLi Y(2024)A framework of fermatean fuzzy cognitive map and its extension based on Hamacher operationEngineering Applications of Artificial Intelligence10.1016/j.engappai.2024.108676136:PAOnline publication date: 1-Oct-2024
https://dl.acm.org/doi/10.1016/j.engappai.2024.108676
Sreepada RPatra B(2022)Mitigating long tail effect in recommendations using few shot learning techniqueExpert Systems with Applications: An International Journal10.1016/j.eswa.2019.112887140:COnline publication date: 21-Apr-2022
https://dl.acm.org/doi/10.1016/j.eswa.2019.112887
Haseena SSaroja SRevathi T(2022)A fuzzy approach for multi criteria decision making in diet plan ranking system using cuckoo optimizationNeural Computing and Applications10.1007/s00521-022-07163-y34:16(13625-13638)Online publication date: 1-Aug-2022
https://dl.acm.org/doi/10.1007/s00521-022-07163-y
Shojaei MSaneifar H(2021)MFSRExpert Systems with Applications: An International Journal10.1016/j.eswa.2021.114969177:COnline publication date: 1-Sep-2021
https://dl.acm.org/doi/10.1016/j.eswa.2021.114969
Manoharan SSenthilkumar R(2020)An Intelligent Fuzzy Rule-Based Personalized News Recommendation Using Social Media MiningComputational Intelligence and Neuroscience10.1155/2020/37915412020Online publication date: 31-May-2020
https://dl.acm.org/doi/10.1155/2020/3791541
Abdeljabar BRahmani LMebrouk BKada B(2020)Estimating daily diffuse solar radiation using neuro-fuzzy, fuzzy C-means and subtractive clusteringProceedings of the 10th International Conference on Information Systems and Technologies10.1145/3447568.3448516(1-6)Online publication date: 4-Jun-2020
https://dl.acm.org/doi/10.1145/3447568.3448516
Papamitsiou ZEconomides A(2020)Motivating Students in Collaborative Activities With Game-Theoretic Group RecommendationsIEEE Transactions on Learning Technologies10.1109/TLT.2018.286958213:2(374-386)Online publication date: 1-Apr-2020
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Singh M(2020)Scalability and sparsity issues in recommender datasets: a surveyKnowledge and Information Systems10.1007/s10115-018-1254-262:1(1-43)Online publication date: 1-Jan-2020
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Rutkowski TNielek RRutkowska DRutkowski L(2020)A Novel Explainable Recommender for Investment ManagersArtificial Intelligence and Soft Computing10.1007/978-3-030-61534-5_37(412-422)Online publication date: 12-Oct-2020
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