AMT-CDR: A Deep Adversarial Multi-channel Transfer Network for Cross-domain Recommendation
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Updated
Nov 2, 2023 - Python
AMT-CDR: A Deep Adversarial Multi-channel Transfer Network for Cross-domain Recommendation
Pre-training and Transfer learning papers for recommendation
Is ID embedding necessary for multimodal recommender system?
Enhanced recommendations through sentiment analysis on reviews and prioritized popular attractions based on keyword frequency, ensuring more personalized and relevant suggestions
A repository listing important datasets for multimodal recommender systems
papers of universal user representation learning for recommendation
Multi-domain Recommendation with Adapter Tuning
Review-Aware Cross Domain Product Recommendation
Context-Aware Residual Transformer (CART) is a kiosk recommendation system (CART) that utilizes self-supervised learning techniques tailored to kiosks in an offline retail environment and developed by a collaboration between NS Lab @ CUK and IIP Lab @ Gachon University based on pure PyTorch backend.
Multimodal Dataset and Benchmark for Multi-domain and Cross-domain Recommendation System
[ICDE 2022]Cross-Domain Recommendation to Cold-Start Users via Variational Information Bottleneck
The source code and dataset for the RecGURU paper (WSDM 2022)
Item Silk Road: Recommending Items from Information Domains to Social Users, SIGIR2017
Paper List of Pre-trained Foundation Recommender Models
This is the official implementation of our paper Personalized Transfer of User Preferences for Cross-domain Recommendation (PTUPCDR), which has been accepted by WSDM2022.
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