A people-to-people content-based reciprocal recommender using hidden markov models
Author:
Affiliation:
1. King Abdulaziz City for Science and Technology, Riyadh, Saudi Arabia
2. The University of New South Wales, Sydney, Australia
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/2507157.2507214
Reference10 articles.
1. Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions
2. People-to-People Recommendation Using Multiple Compatible Subgroups
3. Collaborative filtering with temporal dynamics
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1. Reciprocal Sequential Recommendation;Proceedings of the 17th ACM Conference on Recommender Systems;2023-09-14
2. Generating Popularity-Aware Reciprocal Recommendations Using Siamese Bi-Directional Gated Recurrent Units Network;Vietnam Journal of Computer Science;2023-05-31
3. DCRS: a deep contrast reciprocal recommender system to simultaneously capture user interest and attractiveness for online dating;Neural Computing and Applications;2022-01-17
4. Extracting Users’ Explicit Preferences from Free-text using Second Order Co-occurrence PMI in Indian Matrimony;Procedia Computer Science;2020
5. Recommendation over time: a probabilistic model of time-aware recommender systems;Science China Information Sciences;2019-10-09
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