The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.
Improved Recurrent Neural Networks for Session-based Recommendations
Open accessAbstract
Recurrent neural networks (RNNs) were recently proposed for the session-based recommendation task. The models showed promising improvements over traditional recommendation approaches. In this work, we further study RNN-based models for session-based recommendations. We propose the application of two techniques to improve model performance, namely, data augmentation, and a method to account for shifts in the input data distribution. We also empirically study the use of generalised distillation, and a novel alternative model that directly predicts item embeddings. Experiments on the RecSys Challenge 2015 dataset demonstrate relative improvements of 12.8% and 14.8% over previously reported results on the [email protected] and Mean Reciprocal [email protected] metrics respectively.
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Cites
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Cited by
Session-Based Recommendation with Graph Neural Networks
Wu, S., Tang, Y., Zhu, Y., Wang, L., Xie, X., & Tan, T. (2019) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v33i01.3301346 · Cited by 1,532
When Recurrent Neural Networks meet the Neighborhood for Session-Based Recommendation
Jannach, D., & Ludewig, M. (2017) · Proceedings of the Eleventh ACM Conference on Recommender Systems · doi:10.1145/3109859.3109872 · Cited by 490
RecBole: Towards a Unified, Comprehensive and Efficient Framework for Recommendation Algorithms
Zhao, W. X., Mu, S., Hou, Y., Lin, Z., Chen, Y., Pan, X., Li, K., Lu, Y., Wang, H., Tian, C., et al. (2021) · Proceedings of the 30th ACM International Conference on Information & Knowledge Management · doi:10.1145/3459637.3482016 · Cited by 455
Sequential User-based Recurrent Neural Network Recommendations
Donkers, T., Loepp, B., & Ziegler, J. (2017) · Proceedings of the Eleventh ACM Conference on Recommender Systems · doi:10.1145/3109859.3109877 · Cited by 359
Rethinking the Item Order in Session-based Recommendation with Graph Neural Networks
Qiu, R., Li, J., Huang, Z., & YIn, H. (2019) · Proceedings of the 28th ACM International Conference on Information and Knowledge Management · doi:10.1145/3357384.3358010 · Cited by 339
Metadata
- Authors
- Tan, Y. K., Xu, X., & Liu, Y.
- Venue
- Proceedings of the 1st Workshop on Deep Learning for Recommender Systems
- Publisher
- ACM
- Published
- 2016-09-15
- Pages
- 17-22
- OpenAlex
- W2469952266
- Cited by
- 779
- References
- 12
- FWCI
- 47.29
- Type
- conference paper
- Language
- en
- Open access
- green
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- Tan, Y. K., Xu, X., & Liu, Y. (2016). Improved Recurrent Neural Networks for Session-based Recommendations. Proceedings of the 1st Workshop on Deep Learning for Recommender Systems. https://doi.org/10.1145/2988450.2988452
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