Fuzzy-Weighted Similarity Measures for Memory-Based Collaborative Recommender Systems

Journal of Intelligent Learning Systems and Applications

ISSN Print: 2150-8402
ISSN Online: 2150-8410
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"Fuzzy-Weighted Similarity Measures for Memory-Based Collaborative Recommender Systems"
written by Mohammad Yahya H. Al-Shamri, Nagi H. Al-Ashwal,
published by Journal of Intelligent Learning Systems and Applications, Vol.6 No.1, 2014

has been cited by the following article(s):

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[9]	Using Fuzzy Rating Information for Collaborative Filtering-based Recommender Systems
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[14]	Content Recommendation Algorithm for Intelligent Navigator in Fog Computing Based IoT Environment
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[16]	Utilizing Fuzzy Logic for Recommender Systems
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[19]	Improving Performance of User-Based Collaborative Filtering Recommender Systems Using the Weighted Similarity Method
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[20]	A Similarity Measure using Fuzzy User Rating Patterns in Collaborative Filtering Systems
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[21]	사용자 기반의 협력필터링을 위한 퍼지 논리를 이용한 새로운 유사도 척도
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[25]	A new weighting approach to solve data sparsity problem in collaborative filtering
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[27]	Similarity Measures Using Fuzzified Ratings for Collaborative Filtering.
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[32]	Effect of Collaborative Recommender System Parameters: Common Set Cardinality and the Similarity Measure
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[33]	Rising fascination towards exploration of recommendation systems
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[34]	Effect of Collaborative Recommender System Parameters: Common Set Cardinality and the Similarity Measure.
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[35]	The new similarity measure based on user preference models for collaborative filtering
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[1]	Optimization of fuzzy similarity by genetic algorithm in user‐based collaborative filtering recommender systems Expert Systems, 2022 DOI:10.1111/exsy.12893

[2]	An image recommendation technique based on fuzzy inference system Soft Computing, 2021 DOI:10.1007/s00500-021-05637-0

[3]	A Brief Analysis of Collaborative and Content Based Filtering Algorithms used in Recommender Systems IOP Conference Series: Materials Science and Engineering, 2020 DOI:10.1088/1757-899X/981/2/022008

[4]	Adaptive Instructional Systems Lecture Notes in Computer Science, 2019 DOI:10.1007/978-3-030-22341-0_32

[5]	Content Recommendation Algorithm for Intelligent Navigator in Fog Computing Based IoT Environment IEEE Access, 2019 DOI:10.1109/ACCESS.2019.2912897

[6]	Adaptive Instructional Systems Lecture Notes in Computer Science, 2019 DOI:10.1007/978-3-030-22341-0_32

[7]	A Similarity Measure using Fuzzy User Rating Patterns in Collaborative Filtering Systems 2018 2nd European Conference on Electrical Engineering and Computer Science (EECS), 2018 DOI:10.1109/EECS.2018.00077

[8]	A New Fuzzy Logic-Based Similarity Measure Applied to Large Gap Imputation for Uncorrelated Multivariate Time Series Applied Computational Intelligence and Soft Computing, 2018 DOI:10.1155/2018/9095683

[9]	A New Similarity Measure using Fuzzy Logic for User-based Collaborative Filtering The Journal of Korean Association of Computer Education, 2018 DOI:10.32431/kace.2018.21.5.006

[10]	Collaborative Filtering Using Fuzzy Rank-Based Similarity Measures 2018 International Conference on Control, Artificial Intelligence, Robotics & Optimization (ICCAIRO), 2018 DOI:10.1109/ICCAIRO.2018.00023

[11]	Effect of Collaborative Recommender System Parameters: Common Set Cardinality and the Similarity Measure Advances in Artificial Intelligence, 2016 DOI:10.1155/2016/9386368

[12]	Rising fascination towards exploration of recommendation systems 2016 International Conference on Advanced Communication Control and Computing Technologies (ICACCCT), 2016 DOI:10.1109/ICACCCT.2016.7831742

[13]	The new similarity measure based on user preference models for collaborative filtering 2015 IEEE International Conference on Information and Automation, 2015 DOI:10.1109/ICInfA.2015.7279353

[14]	Power coefficient as a similarity measure for memory-based collaborative recommender systems Expert Systems with Applications, 2014 DOI:10.1016/j.eswa.2014.03.025

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