Repository for implementation of Recsys papers
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Updated
Aug 24, 2023 - Python
Repository for implementation of Recsys papers
[Neurocomputing 2019] Code for "A Hierarchical Contextual Attention-based Network for Sequential Recommendation"
Mindspore Implementation of CIKM 2022 Paper "Disentangling Past-Future Modeling in Sequential Recommendation via Dual Networks"
【KBS】Modeling and Predicting User Preferences with Multiple Item Attributes for Sequential Recommendations
This is the code for "Improving diversity and precision in sequential recommendation via RL"
Official source code for AAAI 2023 paper: Uniform Sequence Better: Time Interval Aware Data Augmentation for Sequential Recommendation. AAAI, 2023.
Master's thesis : Exploiting Latent Interaction Information for Session-Aware Recommendation Using Recurrent Neural Networks ( Recommendation System / Tensorflow / Python )
✨ The Tensorflow implementation for the IEEE Access paper: "ARERec: Attentive Local Interaction Model for Sequential Recommendation".
SOTA models for sequential recommendation
[TKDE 2018] Code for "MV-RNN: A Multi-View Recurrent Neural Network for Sequential Recommendation"
Codebase for RecSys 2024 paper, The Elephant in the Room: Rethinking the Usage of Pre-trained Language Model in Sequential Recommendation
Pytorch implementation of GeoSAN (Geography-Aware Sequential Location Recommendation. KDD 2021)
A configurable Transformer-based model for clickstream data
Implementation of CIKM2022 Paper "Disentangling Past-Future Modeling in Sequential Recommendation via Dual Networks"
Code for TKDE22 paper "Modeling Dynamic User Preference via Dictionary Learning for Sequential Recommendation"
Integrating Item Relevance in Training Loss for Sequential Recommender Systems
[arXiv'24] The official implementation code of LLM-ESR.
Official Code Framework of the paper "Latent Linear Critiquing for Conversational Recommender Systems"
Code for ICML21 paper "Learning Self-Modulating Attention in Continuous Time Space with Applications to Sequential Recommendation"
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