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[FEATURE] Add next-item recommendation models
Description
Expected behavior with the suggested feature
- [ ] ContraRec: "Sequential Recommendation with Multiple Contrast Signals" Wang et al., TOIS'2022.
- [ ] Modeling Contemporaneous Basket Sequences with Twin Networks for Next-Item Recommendation
- [ ] Basket-Sensitive Personalized Item Recommendation
- [ ] Next-item recommendation with sequential hypergraphs
- [ ] A simple convolutional generative network for next item recommendation
- [ ] Learning from history and present: Next-item recommendation via discriminatively exploiting user behaviors
- [ ] Attention-based transactional context embedding for next-item recommendation
- [ ] Next-item recommendation via collaborative filtering with bidirectional item similarity
- [ ] Next item recommendation with self-attentive metric learning
- [ ] Next-item recommendations in short sessions
- [ ] Attentive sequential models of latent intent for next item recommendation
- [ ] Learning a hierarchical intent model for next-item recommendation
- [ ] Sequential modeling of hierarchical user intention and preference for next-item recommendation
- [ ] A lightweight transformer for next-item product recommendation
- [ ] Lighter and better: low-rank decomposed self-attention networks for next-item recommendation
- [ ] Dynamic multi-behavior sequence modeling for next item recommendation
- [ ] DynamicRec: a dynamic convolutional network for next item recommendation
- [ ] Online personalized next-item recommendation via long short term preference learning
- [ ] Transformers4rec: Bridging the gap between nlp and sequential/session-based recommendation
- [ ] Session-based recommendation with graph neural networks
- [ ] Repeatnet: A Repeat Aware Neural Recommendation Machine for Session-based Recommendation
- [ ] Sequential Recommender System based on Hierarchical Attention Network
- [ ] Buy It Again: Modeling Repeat Purchase Recommendations
- [ ] Personalized Category Frequency prediction for Buy It Again recommendations
- [ ] SHARE: Session-based Recommendation with Hypergraph Attention Networks
- [ ] Multi-behavior hypergraph-enhanced transformer for sequential recommendation
Other Comments
It's a comprehensive list of models. To implement all of them is a tremendous amount of efforts. Do we have any criteria to prioritize them?