[FEATURE] Add next-basket recommendation models

[lthoang]

Description

Expected behavior with the suggested feature

• [x] GPTop: including Global top frequent items, Personalized top frequent items, and both. https://dl.acm.org/doi/pdf/10.1145/3587153
• [x] TIFUKNN: Modeling Personalized Item Frequency Information for Next-basket Recommendation
• [ ] Time-Dependent Next-Basket Recommendations (TIFUKNN-TA, TIFUKNN-TD)
• [x] Beacon: Correlation-Sensitive Next-Basket Recommendation
• [x] UP-CF@r: Recency aware collaborative filtering for next basket recommendation
• [ ] Dream: A Dynamic Recurrent Model for Next Basket Recommendation
• [ ] Sets2Sets: Learning from Sequential Sets with Neural Networks
• [x] DNNTSP: Predicting Temporal Sets with Deep Neural Networks
• [ ] CLEA: The world is binary: Contrastive learning for denoising next basket recommendation
• [ ] M2: Mixed Models with Preferences, Popularities and Transitions for Next-Basket Recommendation
• [ ] Time-Aware Item Weighting for the Next Basket Recommendations
• [ ] Masked and Swapped Sequence Modeling for Next Novel Basket Recommendation in Grocery Shopping
• [ ] FPMC: Factorizing personalized markov chains for next-basket recommendation, code: https://github.com/khesui/FPMC
• [ ] Personalized Category Frequency prediction for Buy It Again recommendations
• [ ] ReCANet: A repeat consumption-aware neural network for next basket recommendation in grocery shopping
• [ ] DigBot: Next Basket Recommendation with Intent-aware Hypergraph Adversarial Network
• [ ] BRL: Basket Representation Learning by Hypergraph Convolution on Repeated Items for Next-basket Recommendation
• [ ] MMNR: Multi-view Multi-aspect Neural Networks for Next-basket Recommendation, code https://github.com/Hiiizhy/MMNR

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