The DOI matches its Crossref record; 44 of the 44 references it cites were found in a registry or an index.
Latent Cross: Making Use of Context in Recurrent Recommender Systems
Open accessAbstract
The success of recommender systems often depends on their ability to understand and make use of the context of the recommendation request. Significant research has focused on how time, location, interfaces, and a plethora of other contextual features affect recommendations. However, in using deep neural networks for recommender systems, researchers often ignore these contexts or incorporate them as ordinary features in the model.
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Cites
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Neural Collaborative Filtering
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Self-citationWide & Deep Learning for Recommender Systems
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Tabular data: Deep learning is not all you need
Shwartz-Ziv, R., & Armon, A. (2022) · Information Fusion · doi:10.1016/j.inffus.2021.11.011 · Cited by 2,172
Time Interval Aware Self-Attention for Sequential Recommendation
Li, J., Wang, Y., & McAuley, J. (2020) · Proceedings of the 13th International Conference on Web Search and Data Mining · doi:10.1145/3336191.3371786 · Cited by 649
Self-citationDeep Item-based Collaborative Filtering for Top-N Recommendation
Xue, F., He, X., Wang, X., Xu, J., Liu, K., & Hong, R. (2019) · ACM Transactions on Information Systems · doi:10.1145/3314578 · Cited by 339
Representation learning for dynamic graphs: A survey
Kazemi, S. M., Goel, R., Jain, K., Kobyzev, I., Sethi, A., Forsyth, P., & Poupart, P. (2019) · arXiv · doi:10.48550/arxiv.1905.11485 · Cited by 338
Chen, X., Chen, H., Xu, H., Zhang, Y., Cao, Y., Qin, Z., & Zha, H. (2019) · Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval · doi:10.1145/3331184.3331254 · Cited by 284
Metadata
- Authors
- Beutel, A., Covington, P., Jain, S., Xu, C., Li, J., Gatto, V., & Chi, E. H.
- Venue
- Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining
- Publisher
- ACM
- Published
- 2018-02-02
- Pages
- 46-54
- OpenAlex
- W2773640334
- Cited by
- 313
- References
- 44
- FWCI
- 36.47
- Type
- conference paper
- Language
- en
- Open access
- hybrid
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- CoChat. (2026). Citation check: Latent Cross: Making Use of Context in Recurrent Recommender Systems. https://app.cochat.ai/papers/10.1145/3159652.3159727
- The paper
- Beutel, A., Covington, P., Jain, S., Xu, C., Li, J., Gatto, V., & Chi, E. H. (2018). Latent Cross: Making Use of Context in Recurrent Recommender Systems. Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining. https://doi.org/10.1145/3159652.3159727
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