Collaborative Filtering

Collaborative filtering (CF) is a core technique in recommender systems aiming to predict user preferences by leveraging past user-item interactions. Current research emphasizes improving CF's accuracy and efficiency, particularly addressing challenges like cold-start problems (limited user data) and biases (favoring popular items or user groups), through advancements in model architectures such as graph neural networks, diffusion models, and autoencoders, as well as refined loss functions and sampling strategies. These improvements are crucial for enhancing the personalization and fairness of recommendation systems across diverse applications, from e-commerce and social media to specialized domains like course selection and real estate.

Papers

November 14, 2024

DeBaTeR: Denoising Bipartite Temporal Graph for Recommendation
Xinyu He, Jose Sepulveda, Mostafa Rahmani, Alyssa Woo, Fei Wang, Hanghang Tong
Effective Recommendation Temporal Graph Collaborative Filtering Implicit Feedback Debate Evaluation

November 3, 2024

Co-clustering for Federated Recommender System
Xinrui He, Shuo Liu, Jackey Keung, Jingrui He
Recommender System Federated Prompt Cooperation Collaborative Filtering Client Heterogeneity Federated Recommendation Co Segmentation

November 2, 2024

Online and Offline Evaluations of Collaborative Filtering and Content Based Recommender Systems
Ali Elahi, Armin Zirak
Recommender System Collaborative Filtering Online Service Offline Evaluation Item Based Collaborative Filtering Large Scale Recommendation

November 1, 2024

LLM-KT: A Versatile Framework for Knowledge Transfer from Large Language Models to Collaborative Filtering
Nikita Severin, Aleksei Ziablitsev, Yulia Savelyeva, Valeriy Tashchilin, Ivan Bulychev, Mikhail Yushkov, Artem Kushneruk, Amaliya Zaryvnykh, Dmitrii Kiselev, Andrey Savchenko, Ilya Makarov
Full Model Jina Embeddings Knowledge Transfer Large Language Collaborative Filtering Flexible Framework Context Awareness Recommendation Scenario Knowledge Management

October 25, 2024

TEARS: Textual Representations for Scrutable Recommendations
Emiliano Penaloza, Olivier Gouvert, Haolun Wu, Laurent Charlin
Collaborative Filtering Textual Representation Traditional Recommender Tear Film Controllable Text Recommendation

October 15, 2024

Understanding and Scaling Collaborative Filtering Optimization from the Perspective of Matrix Rank
Donald Loveland, Xinyi Wu, Tong Zhao, Danai Koutra, Neil Shah, Mingxuan Ju
Real World Human Understanding Visual Perspective Collaborative Filtering Item Embeddings Large Scale Recommender System Low Rank Regularization Performance Guaranteed Regularization

October 14, 2024

Collaborative filtering based on nonnegative/binary matrix factorization
Yukino Terui, Yuka Inoue, Yohei Hamakawa, Kosuke Tatsumura, Kazue Kudo
Matrix Factorization Collaborative Filtering Recommendation Performance

October 4, 2024

September 29, 2024

DiffCP: Ultra-Low Bit Collaborative Perception via Diffusion Model
Ruiqing Mao, Haotian Wu, Yukuan Jia, Zhaojun Nan, Yuxuan Sun, Sheng Zhou, Deniz Gündüz, Zhisheng Niu
Diffusion Model Collaborative Filtering Collaborative Perception Communication Cost Feature Swapping

September 26, 2024

A Multimodal Single-Branch Embedding Network for Recommendation in Cold-Start and Missing Modality Scenarios
Christian Ganhör, Marta Moscati, Anna Hausberger, Shah Nawaz, Markus Schedl
Network Programming Effective Recommendation Multimodal Learning Multimodal Information Collaborative Filtering Missing Modality Multimodal Capability Cold Start Multimodal Recommendation

September 23, 2024

EDGE-Rec: Efficient and Data-Guided Edge Diffusion For Recommender Systems Graphs
Utkarsh Priyam, Hemit Shah, Edoardo Botta
Extreme Edge Graph Based Collaborative Filtering Weight Matrix User Item

September 21, 2024

The trade-off between data minimization and fairness in collaborative filtering
Nasim Sonboli, Sipei Li, Mehdi Elahi, Asia Biega
Active Learning Recommender System Procedural Fairness Collaborative Filtering Data Minimization

September 2, 2024

Improved Diversity-Promoting Collaborative Metric Learning for Recommendation
Shilong Bao, Qianqian Xu, Zhiyong Yang, Yuan He, Xiaochun Cao, Qingming Huang
Effective Recommendation Recommendation System Metric Learning Collaborative Filtering Diversity Regularizer Collaborative Metric Learning

August 25, 2024

CF-KAN: Kolmogorov-Arnold Network-based Collaborative Filtering to Mitigate Catastrophic Forgetting in Recommender Systems
Jin-Duk Park, Kyung-Min Kim, Won-Yong Shin
Continual LEArning Recommender System Catastrophic Forgetting Kolmogorov Arnold Network Collaborative Filtering Recommendation Accuracy

August 22, 2024

Fair Augmentation for Graph Collaborative Filtering
Ludovico Boratto, Francesco Fabbri, Gianni Fenu, Mirko Marras, Giacomo Medda
Collaborative Filtering User Item Fair Graph Graph Collaborative Filtering

August 16, 2024

Personalized Federated Collaborative Filtering: A Variational AutoEncoder Approach
Zhiwei Li, Guodong Long, Tianyi Zhou, Jing Jiang, Chengqi Zhang
Collaborative Filtering Federated Recommendation FedCF Method

July 19, 2024

L^2CL: Embarrassingly Simple Layer-to-Layer Contrastive Learning for Graph Collaborative Filtering
Xinzhou Jin, Jintang Li, Liang Chen, Chenyun Yu, Yuanzhen Xie, Tao Xie, Chengxiang Zhuo, Zang Li, Zibin Zheng
Contrastive Learning Collaborative Filtering Graph Augmentation Graph Collaborative Filtering

July 18, 2024

A Comprehensive Review of Recommender Systems: Transitioning from Theory to Practice
Shaina Raza, Mizanur Rahman, Safiullah Kamawal, Armin Toroghi, Ananya Raval, Farshad Navah, Amirmohammad Kazemeini
Recommender System Theoretical Understanding Comprehensive Review Collaborative Filtering User Perception Personalized Image Fairness Aware Recommender System

July 13, 2024

SocialRec: User Activity Based Post Weighted Dynamic Personalized Post Recommendation System in Social Media
Ismail Hossain, Sai Puppala, Md Jahangir Alam, Sajedul Talukder
Social Medium Recommendation System Collaborative Filtering Social Medium Platform Recommendation Quality Similarity Score User Profile

Collaborative Filtering

Papers

DeBaTeR: Denoising Bipartite Temporal Graph for Recommendation

Co-clustering for Federated Recommender System

Online and Offline Evaluations of Collaborative Filtering and Content Based Recommender Systems

LLM-KT: A Versatile Framework for Knowledge Transfer from Large Language Models to Collaborative Filtering

TEARS: Textual Representations for Scrutable Recommendations

Understanding and Scaling Collaborative Filtering Optimization from the Perspective of Matrix Rank

Collaborative filtering based on nonnegative/binary matrix factorization

Explaining the (Not So) Obvious: Simple and Fast Explanation of STAN, a Next Point of Interest Recommendation System

Geometric Collaborative Filtering with Convergence

DiffCP: Ultra-Low Bit Collaborative Perception via Diffusion Model

A Multimodal Single-Branch Embedding Network for Recommendation in Cold-Start and Missing Modality Scenarios

EDGE-Rec: Efficient and Data-Guided Edge Diffusion For Recommender Systems Graphs

The trade-off between data minimization and fairness in collaborative filtering

Improved Diversity-Promoting Collaborative Metric Learning for Recommendation

CF-KAN: Kolmogorov-Arnold Network-based Collaborative Filtering to Mitigate Catastrophic Forgetting in Recommender Systems

Fair Augmentation for Graph Collaborative Filtering

Personalized Federated Collaborative Filtering: A Variational AutoEncoder Approach

L^2CL: Embarrassingly Simple Layer-to-Layer Contrastive Learning for Graph Collaborative Filtering

A Comprehensive Review of Recommender Systems: Transitioning from Theory to Practice

SocialRec: User Activity Based Post Weighted Dynamic Personalized Post Recommendation System in Social Media