Fuzzy Norm-Explicit Product Quantization for Recommender Systems
International Journal
Year of publication
2024
Volume
32
Issue
5
Pagination
2987-2998
DOI
10.1109/TFUZZ.2024.3365722
Journal
IEEE Transactions on Fuzzy Systems
Jamalifard, M., et al. «Fuzzy Norm-Explicit Product Quantization For Recommender Systems». Ieee Transactions On Fuzzy Systems, 2024, pp. 2987-2998.
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Creating synthetic datasets for collaborative filtering recommender systems using generative adversarial networks
International Journal
Year of publication
2023
Volume
280
Pagination
111016
DOI
https://doi.org/10.1016/j.knosys.2023.111016
Journal
Knowledge-Based Systems
ISSN Number
0950-7051
URL
https://www.sciencedirect.com/science/article/pii/S0950705123007669
Bobadilla, J., et al. «Creating Synthetic Datasets For Collaborative Filtering Recommender Systems Using Generative Adversarial Networks». Knowledge-Based Systems, 2023, p. 111016.
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A Big Data Semantic Driven Context Aware Recommendation Method for Question-Answer Items
International Journal
Year of publication
2019
Volume
7
Issue
1
Pagination
182664-182678
DOI
10.1109/ACCESS.2019.2957881
Journal
IEEE Access
ISSN Number
2169-3536
Castro, J., et al. «A Big Data Semantic Driven Context Aware Recommendation Method For Question-Answer Items». Ieee Access, 2019, pp. 182664-182678.
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A food recommender system considering nutritional information and user preferences
International Journal
Year of publication
2019
Volume
7
Issue
1
Pagination
96695-96711
DOI
10.1109/ACCESS.2019.2929413
Journal
IEEE Access
Date Published
12/2019
ISSN Number
2169-3536
Yera, R., et al. «A Food Recommender System Considering Nutritional Information And User Preferences». 12/2019d. C. Ieee Access, 2019, pp. 96695-96711.
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Managing Natural Noise in Recommender Systems
Year of publication
2016
Conference Name
5th International Conference on Theory and Practice of Natural Computing (TPNC 2016)
Pagination
3-17
Publisher
Springer
Place Published
Sendai (Japan)
ISSN Number
0302-9743
ISBN Number
978-3-319-49000-7
URL
https://link.springer.com/book/10.1007/978-3-319-49001-4
DOI
10.1007/978-3-319-49001-4
Martínez, L., et al. «Managing Natural Noise In Recommender Systems». 5Th International Conference On Theory And Practice Of Natural Computing (Tpnc 2016), Springer, 2016, pp. 3-17.
International Conference
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Regularizing Knowledge Transfer in Recommendation With Tag-Inferred Correlation
International Journal
Year of publication
2019
Volume
49
Issue
1
Pagination
83-96
DOI
10.1109/TCYB.2017.2764918
Journal
IEEE Transactions on Cybernetics
ISSN Number
2168-2267
Hao, P., et al. «Regularizing Knowledge Transfer In Recommendation With Tag-Inferred Correlation». Ieee Transactions On Cybernetics, 2019, pp. 83-96.
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Correcting noisy ratings in collaborative recommender systems
International Journal
Year of publication
2015
Publisher
Elsevier
Volume
76
Pagination
96-108
Journal
Knowledge-based Systems
URL
http://dx.doi.org/10.1016/j.knosys.2014.12.011
Yera, R., et al. «Correcting Noisy Ratings In Collaborative Recommender Systems». Knowledge-Based Systems, Elsevier, 2015, pp. 96-108.
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1
Weighting of Features in Content-Based Filtering with Entropy and Dependence Measures
International Journal
Year of publication
2014
Publisher
Taylor and Francis
Volume
7
Pagination
80-89
Journal
International Journal of Computational Intelligence Systems
Number
1
URL
http://dx.doi.org/10.1080/18756891.2013.859861
Castro, J., et al. «Weighting Of Features In Content-Based Filtering With Entropy And Dependence Measures». International Journal Of Computational Intelligence Systems, 1, Taylor and Francis, 2014, pp. 80-89.
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A fuzzy approach for natural noise management in group recommender systems
International Journal
Year of publication
2018
Volume
94
Pagination
237-249
DOI
https://doi.org/10.1016/j.eswa.2017.10.060
Journal
Expert Systems with Applications
Date Published
03/ 2018
ISSN Number
0957-4174
URL
https://www.sciencedirect.com/science/article/pii/S095741741730742X
Castro, J., et al. «A Fuzzy Approach For Natural Noise Management In Group Recommender Systems». 03/ 2018d. C. Expert Systems With Applications, 2018, pp. 237-249.
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An empirical study of natural noise management in group recommendation systems
International Journal
Year of publication
2017
Volume
94
Pagination
1-11
DOI
http://dx.doi.org/10.1016/j.dss.2016.09.020
Journal
Decision Support Systems
Date Published
02/2017
ISSN Number
0167-9236
URL
http://www.sciencedirect.com/science/article/pii/S0167923616301695
Castro, J., et al. «An Empirical Study Of Natural Noise Management In Group Recommendation Systems». 02/2017d. C. Decision Support Systems, 2017, pp. 1-11.
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