Recommendation Model

Recommendation models aim to predict user preferences and provide personalized suggestions, primarily focusing on improving accuracy, efficiency, and fairness. Current research emphasizes addressing challenges like data sparsity, cold starts, popularity bias, and the impact of noisy data through techniques such as multi-modal approaches, knowledge graph integration, attention mechanisms, and self-supervised learning. These advancements have significant implications for various applications, including e-commerce, entertainment, and even healthcare, by enhancing user experience and enabling more effective information filtering.

Papers

January 7, 2024

ChatGPT for Conversational Recommendation: Refining Recommendations by Reprompting with Feedback
Kyle Dylan Spurlock, Cagla Acun, Esin Saka, Olfa Nasraoui
ChatGPT Generated Conversation Human Feedback Movie Recommendation Recommendation Model Recommendation Algorithm Conversational Recommendation Popularity Bias Conversational Recommender System Refining Method

January 3, 2024

Studying and Recommending Information Highlighting in Stack Overflow Answers
Shahla Shaan Ahmed, Shaowei Wang, Yuan Tian, Tse-Hsun, Chen, Haoxiang Zhang
Entity Recognition Recommendation Model Stack Overflow Semantic Markup

December 20, 2023

BSL: Understanding and Improving Softmax Loss for Recommendation
Junkang Wu, Jiawei Chen, Jiancan Wu, Wentao Shi, Jizhi Zhang, Xiang Wang
Loss Function Human Understanding Effective Recommendation Recommendation Model Distributionally Robust Optimization Softmax Loss

November 27, 2023

A Social-aware Gaussian Pre-trained Model for Effective Cold-start Recommendation
Siwei Liu, Xi Wang, Craig Macdonald, Iadh Ounis
Pre Trained Model Recommender System Recommendation Model Pre Training Model Novel Recommendation

November 18, 2023

RecExplainer: Aligning Large Language Models for Explaining Recommendation Models
Yuxuan Lei, Jianxun Lian, Jing Yao, Xu Huang, Defu Lian, Xing Xie
Recommender System Recommendation Model Alignment Objective

November 15, 2023

User Persona Identification and New Service Adaptation Recommendation
Narges Tabari, Sandesh Swamy, Rashmi Gangadharaiah
Recommendation Model Item Based Collaborative Filtering Neural Collaborative Filtering User Trajectory User Persona

November 12, 2023

Alleviating Behavior Data Imbalance for Multi-Behavior Graph Collaborative Filtering
Yijie Zhang, Yuanchen Bei, Shiqi Yang, Hao Chen, Zhiqing Li, Lijia Chen, Feiran Huang
Collaborative Filtering Recommendation Model Recommendation Performance Data Imbalance Multi Behavior

November 10, 2023

DPR: An Algorithm Mitigate Bias Accumulation in Recommendation feedback loops
Hangtong Xu, Yuanbo Xu, Yongjian Yang, Fuzhen Zhuang, Hui Xiong
Recommendation System Recommendation Model Negative Sampling Recommendation Quality Bias Amplification Bias Mitigation Algorithm

November 4, 2023

CDR-Adapter: Learning Adapters to Dig Out More Transferring Ability for Cross-Domain Recommendation Models
Yanyu Chen, Yao Yao, Wai Kin Victor Chan, Li Xiao, Kai Zhang, Liang Zhang, Yun Ye
Knowledge Transfer Recommendation System Recommendation Model Recommendation Performance Cross Domain Recommendation Adapter Learning

November 3, 2023

Heterogeneous federated collaborative filtering using FAIR: Federated Averaging in Random Subspaces
Aditya Desai, Benjamin Meisburger, Zichang Liu, Anshumali Shrivastava
Recommendation System Collaborative Filtering Recommendation Model Federated Averaging Heterogeneous Setting Neural Collaborative Filtering Random Subspace

October 18, 2023

Federated Heterogeneous Graph Neural Network for Privacy-preserving Recommendation
Bo Yan, Yang Cao, Haoyu Wang, Wenchuan Yang, Junping Du, Chuan Shi
Differential Privacy Recommender System Effective Recommendation Recommendation Model Heterogeneous Graph Neural Network Heterogeneous Information Network Heterogeneous Recommendation

October 7, 2023

Ten Challenges in Industrial Recommender Systems
Zhenhua Dong, Jieming Zhu, Weiwen Liu, Ruiming Tang
Recommender System Recommendation Model Industrial Recommender System

October 6, 2023

On the Embedding Collapse when Scaling up Recommendation Models
Xingzhuo Guo, Junwei Pan, Ximei Wang, Baixu Chen, Jie Jiang, Mingsheng Long
Recommendation Model Event Collapse Multiple Embeddings Large Scale Recommender System Scalable Model

August 28, 2023

Ad-Rec: Advanced Feature Interactions to Address Covariate-Shifts in Recommendation Networks
Muhammad Adnan, Yassaman Ebrahimzadeh Maboud, Divya Mahajan, Prashant J. Nair
Recommendation Model Covariate Shift Recommendation Task Feature Interaction Deep Recommendation

August 27, 2023

Text Matching Improves Sequential Recommendation by Reducing Popularity Biases
Zhenghao Liu, Sen Mei, Chenyan Xiong, Xiaohua Li, Shi Yu, Zhiyuan Liu, Yu Gu, Ge Yu
Recommendation System Sequential Recommendation Recommendation Model Recommendation Accuracy Popularity Bias Text Matching

August 21, 2023

Graph Neural Bandits
Yunzhe Qi, Yikun Ban, Jingrui He
Recommendation Model Bandit Algorithm Contextual Bandit Algorithm Recommendation Scenario

August 17, 2023

A Model-Agnostic Framework for Recommendation via Interest-aware Item Embeddings
Amit Kumar Jaiswal, Yu Xiong
Effective Recommendation Recommendation Model Capsule Network Model Agnostic Item Representation Item Embeddings Interest Representation

August 14, 2023

UIPC-MF: User-Item Prototype Connection Matrix Factorization for Explainable Collaborative Filtering
Lei Pan, Von-Wun Soo
High Explainability Matrix Factorization Recommendation Model Explainable Recommender System Interaction Data

August 10, 2023

SSLRec: A Self-Supervised Learning Framework for Recommendation
Xubin Ren, Lianghao Xia, Yuhao Yang, Wei Wei, Tianle Wang, Xuheng Cai, Chao Huang
Self Supervised Supervised Learning Effective Recommendation Recommendation Model Recommendation Algorithm Self Supervised Learning Framework

August 7, 2023

Heterogeneous Knowledge Fusion: A Novel Approach for Personalized Recommendation via LLM
Bin Yin, Junjie Xie, Yu Qin, Zixiang Ding, Zhichao Feng, Xiang Li, Wei Lin
Large Language Model Novel Approach Recommendation Model Personalized Recommendation Recommendation Performance Heterogeneous Knowledge

Recommendation Model

Papers

ChatGPT for Conversational Recommendation: Refining Recommendations by Reprompting with Feedback

Studying and Recommending Information Highlighting in Stack Overflow Answers

BSL: Understanding and Improving Softmax Loss for Recommendation

A Social-aware Gaussian Pre-trained Model for Effective Cold-start Recommendation

RecExplainer: Aligning Large Language Models for Explaining Recommendation Models

User Persona Identification and New Service Adaptation Recommendation

Alleviating Behavior Data Imbalance for Multi-Behavior Graph Collaborative Filtering

DPR: An Algorithm Mitigate Bias Accumulation in Recommendation feedback loops

CDR-Adapter: Learning Adapters to Dig Out More Transferring Ability for Cross-Domain Recommendation Models

Heterogeneous federated collaborative filtering using FAIR: Federated Averaging in Random Subspaces

Federated Heterogeneous Graph Neural Network for Privacy-preserving Recommendation

Ten Challenges in Industrial Recommender Systems

On the Embedding Collapse when Scaling up Recommendation Models

Ad-Rec: Advanced Feature Interactions to Address Covariate-Shifts in Recommendation Networks

Text Matching Improves Sequential Recommendation by Reducing Popularity Biases

Graph Neural Bandits

A Model-Agnostic Framework for Recommendation via Interest-aware Item Embeddings

UIPC-MF: User-Item Prototype Connection Matrix Factorization for Explainable Collaborative Filtering

SSLRec: A Self-Supervised Learning Framework for Recommendation

Heterogeneous Knowledge Fusion: A Novel Approach for Personalized Recommendation via LLM