Recommendation Datasets

Recommendation datasets are crucial for developing and evaluating algorithms that personalize suggestions for users across various domains, from e-commerce to music streaming. Current research emphasizes improving model accuracy and efficiency by incorporating sequential user interactions, leveraging pre-trained language models and knowledge distillation for lightweight inference, and addressing challenges like data sparsity and cold-start problems through techniques such as test-time training and graph-based regularization. The development of large-scale, diverse datasets, including those reflecting consumer-to-consumer interactions and mobile app usage, is vital for advancing the field and enabling more robust and realistic evaluations of recommendation systems. This work ultimately impacts the user experience and business outcomes of many online platforms.

Papers

October 26, 2024

FLOW: A Feedback LOop FrameWork for Simultaneously Enhancing Recommendation and User Agents
Shihao Cai, Jizhi Zhang, Keqin Bao, Chongming Gao, Fuli Feng
Effective Recommendation Recommendation Performance Flow Mood Feedback Loop Recommendation Datasets

October 17, 2024

Pseudo Dataset Generation for Out-of-Domain Multi-Camera View Recommendation
Kuan-Ying Lee, Qian Zhou, Klara Nahrstedt
Multi View Effective Recommendation Multi Camera Multiple Camera Recommendation Datasets Unknown Out of Domain Pseudo Labeled

September 27, 2024

TTT4Rec: A Test-Time Training Approach for Rapid Adaption in Sequential Recommendation
Zhaoqi Yang, Yanan Wang, Yong Ge
Sequential Recommendation Fast Adaptation Test Time Training Recommendation Datasets Interaction Sequence

September 23, 2024

Pre-trained Language Model and Knowledge Distillation for Lightweight Sequential Recommendation
Li Li, Mingyue Cheng, Zhiding Liu, Hao Zhang, Qi Liu, Enhong Chen
Knowledge Distillation Sequential Recommendation Sequential Recommender System Recommendation Datasets

August 21, 2024

Sliding Window Training -- Utilizing Historical Recommender Systems Data for Foundation Models
Swanand Joshi, Yesu Feng, Ko-Jen Hsiao, Zhe Zhang, Sudarshan Lamkhede
Foundation Model Short Term Sliding Window Recommendation Datasets User Item Interaction

June 20, 2024

Optimizing Novelty of Top-k Recommendations using Large Language Models and Reinforcement Learning
Amit Sharma, Hua Li, Xue Li, Jian Jiao
Reinforcement Learning Human Feedback Recommendation System Recommendation Model Novelty Search Large Scale Search Recommendation Datasets Top N Recommendation

February 28, 2024

Graph Regularized Encoder Training for Extreme Classification
Anshul Mittal, Shikhar Mohan, Deepak Saini, Suchith C. Prabhu, Jain jiao, Sumeet Agarwal, Soumen Chakrabarti, Purushottam Kar, Manik Varma
Computational Cost Recommendation Datasets Encoder Architecture Extreme Classification Graph Regularized Neural Network

February 22, 2024

MerRec: A Large-scale Multipurpose Mercari Dataset for Consumer-to-Consumer Recommendation Systems
Lichi Li, Zainul Abi Din, Zhen Tan, Sam London, Tianlong Chen, Ajay Daptardar
Recommendation System E Commerce Recommendation Task Recommendation Datasets Consumer Generated Medium

November 8, 2023

Decentralized Personalized Online Federated Learning
Renzhi Wu, Saayan Mitra, Xiang Chen, Anup Rao
Personalized Federated Learning Local Model Personalized Model Recommendation Datasets

October 11, 2023

Non-Stationary Contextual Bandit Learning via Neural Predictive Ensemble Sampling
Zheqing Zhu, Yueyang Liu, Xu Kuang, Benjamin Van Roy
Ensemble Learning Contextual Bandit Non Stationary Non Stationarity Recommendation Datasets

July 31, 2023

An Efficient Recommendation System in E-commerce using Passer learning optimization based on Bi-LSTM
Hemn Barzan Abdalla, Awder Ahmed, Bahtiyar Mehmed, Mehdi Gheisari, Maryam Cheraghy
Optimization Purpose E Commerce Bi LSTM Recommendation Datasets Efficient Recommender System Bi LSTM CRF

June 30, 2023

Of Spiky SVDs and Music Recommendation
Darius Afchar, Romain Hennequin, Vincent Guigue
Singular Value Decomposition Music Recommendation Recommendation Datasets Truncated Singular Value Decomposition

March 17, 2023

Explaining the Performance of Collaborative Filtering Methods With Optimal Data Characteristics
Samin Poudel, Marwan Bikdash
System Performance Collaborative Filtering Human Rating User Item Recommendation Datasets Music Datasets Optimal Data

March 12, 2023

MobileRec: A Large-Scale Dataset for Mobile Apps Recommendation
M. H. Maqbool, Umar Farooq, Adib Mosharrof, A. B. Siddique, Hassan Foroosh
Large Scale Dataset Mobile Application Mobile User Recommendation Datasets

March 11, 2023

Uncertainty-Aware Instance Reweighting for Off-Policy Learning
Xiaoying Zhang, Junpu Chen, Hongning Wang, Hong Xie, Yang Liu, John C. S. Lui, Hang Li
Policy OpTimization Policy Learning Recommendation Datasets Inverse Propensity Instance Weighting

October 12, 2022

Simulated Contextual Bandits for Personalization Tasks from Recommendation Datasets
Anton Dereventsov, Anton Bibin
Contextual Bandit User Behavior Recommendation Datasets Personalization Task Personalization System

October 9, 2022

A Spectral Approach to Item Response Theory
Duc Nguyen, Anderson Zhang
Item Response Theory Spectral Method Recommendation Datasets Novel Estimator

September 12, 2022

Ordinal Graph Gamma Belief Network for Social Recommender Systems
Dongsheng Wang, Chaojie Wang, Bo Chen, Mingyuan Zhou
Recommender System Latent Factor Recommendation Datasets Social Recommendation Gamma Belief Network

April 22, 2022

Exploiting Session Information in BERT-based Session-aware Sequential Recommendation
Jinseok Seol, Youngrok Ko, Sang-goo Lee
Sequential Recommendation BERT Based Recommendation Performance Recommendation Datasets Sequence Representation Session Representation

April 4, 2022

CARCA: Context and Attribute-Aware Next-Item Recommendation via Cross-Attention
Ahmed Rashed, Shereen Elsayed, Lars Schmidt-Thieme
Context Information Cross Attention Sequential Recommendation Recommendation Datasets Next Item

Recommendation Datasets

Papers

FLOW: A Feedback LOop FrameWork for Simultaneously Enhancing Recommendation and User Agents

Pseudo Dataset Generation for Out-of-Domain Multi-Camera View Recommendation

TTT4Rec: A Test-Time Training Approach for Rapid Adaption in Sequential Recommendation

Pre-trained Language Model and Knowledge Distillation for Lightweight Sequential Recommendation

Sliding Window Training -- Utilizing Historical Recommender Systems Data for Foundation Models

Optimizing Novelty of Top-k Recommendations using Large Language Models and Reinforcement Learning

Graph Regularized Encoder Training for Extreme Classification

MerRec: A Large-scale Multipurpose Mercari Dataset for Consumer-to-Consumer Recommendation Systems

Decentralized Personalized Online Federated Learning

Non-Stationary Contextual Bandit Learning via Neural Predictive Ensemble Sampling

An Efficient Recommendation System in E-commerce using Passer learning optimization based on Bi-LSTM

Of Spiky SVDs and Music Recommendation

Explaining the Performance of Collaborative Filtering Methods With Optimal Data Characteristics

MobileRec: A Large-Scale Dataset for Mobile Apps Recommendation

Uncertainty-Aware Instance Reweighting for Off-Policy Learning

Simulated Contextual Bandits for Personalization Tasks from Recommendation Datasets

A Spectral Approach to Item Response Theory

Ordinal Graph Gamma Belief Network for Social Recommender Systems

Exploiting Session Information in BERT-based Session-aware Sequential Recommendation

CARCA: Context and Attribute-Aware Next-Item Recommendation via Cross-Attention