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Proceedings of the 13th ACM Conference on Recommender Systems
Abstract
RecSys brings together academia and industry, research and practice, and multiple disciplines including human-computer interaction, machine learning, information retrieval, business, and psychology to advance recommendation techniques and our understanding of their human dimensions.
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Cited by
Gorwa, R., Binns, R., & Katzenbach, C. (2020) · Big Data & Society · doi:10.1177/2053951719897945 · Cited by 1,097
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Khosravi, H., Shum, S. B., Chen, G., Conati, C., Tsai, Y.-S., Kay, J., Knight, S., Martinez-Maldonado, R., Sadiq, S., & Gašević, D. (2022) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2022.100074 · Cited by 863
Himeur, Y., Sohail, S. S., Bensaali, F., Amira, A., & Alazab, M. (2022) · Computers & Security · doi:10.1016/j.cose.2022.102746 · Cited by 139
Pedreschi, D., Pappalardo, L., Ferragina, E., Baeza-Yates, R., Barabási, A.-L., Dignum, F., Dignum, V., Eliassi-Rad, T., Giannotti, F., Kertész, J., et al. (2025) · Artificial Intelligence · doi:10.1016/j.artint.2024.104244 · Cited by 102
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Deep Learning Models for Serendipity Recommendations: A Survey and New Perspectives
Fu, Z., Niu, X., & Maher, M. L. (2024) · ACM Computing Surveys · doi:10.1145/3605145 · Cited by 30
Misztal-Radecka, J., & Indurkhya, B. (2021) · Information Processing & Management · doi:10.1016/j.ipm.2021.102519 · Cited by 29
Neural graph personalized ranking for Top-N Recommendation
Hu, Z., Wang, J., Yan, Y., Zhao, P., Chen, J., & Huang, J. (2021) · Knowledge-Based Systems · doi:10.1016/j.knosys.2020.106426 · Cited by 21
Metadata
- Publisher
- ACM
- Published
- 2019-09-10
- OpenAlex
- W2914576582
- Cited by
- 366
- References
- 0
- Type
- paratext
- Language
- en
- Open access
- closed
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
