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A Revisiting Study of Appropriate Offline Evaluation for Top- N Recommendation Algorithms
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Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/3-540-44801-2_15openalex-snapshot
RecTree: An Efficient Collaborative Filtering Method
inferredcites →https://doi.org/10.1007/978-0-387-85820-3_1openalex-snapshot
Introduction to Recommender Systems Handbook
inferredcites →https://doi.org/10.1007/978-0-387-85820-3_8openalex-snapshot
Evaluating Recommendation Systems
inferredcites →https://doi.org/10.1007/978-1-4899-7687-1_891openalex-snapshot
Online Controlled Experiments and A/B Testing
inferredcites →https://doi.org/10.1007/978-3-319-92007-8_34openalex-snapshot
Reproducibility of Experiments in Recommender Systems Evaluation
inferredcites →https://doi.org/10.1007/978-3-642-31178-9_15openalex-snapshot
GPU-Accelerated Non-negative Matrix Factorization for Text Mining
inferredcites →https://doi.org/10.1007/s10791-020-09371-3openalex-snapshot
Offline evaluation options for recommender systems
inferredcites →https://doi.org/10.1007/s11192-021-03909-yopenalex-snapshot
An overview and evaluation of citation recommendation models
inferredcites →https://doi.org/10.1007/s13042-017-0762-9openalex-snapshot
How good your recommender system is? A survey on evaluations in recommendation
inferredcites →https://doi.org/10.1016/s0893-6080(98)00010-0openalex-snapshot
Automatic early stopping using cross validation: quantifying the criteria
inferredcites →https://doi.org/10.1109/cec.2005.1554761openalex-snapshot
Sequential Parameter Optimization
inferredcites →https://doi.org/10.1109/hipc.2018.00014openalex-snapshot
DeepHyper: Asynchronous Hyperparameter Search for Deep Neural Networks
inferredcites →https://doi.org/10.1109/icdm.2008.16openalex-snapshot
One-Class Collaborative Filtering
inferredcites →https://doi.org/10.1109/icdm.2008.22openalex-snapshot
Collaborative Filtering for Implicit Feedback Datasets
inferredcites →https://doi.org/10.1109/isca45697.2020.00084openalex-snapshot
DeepRecSys: A System for Optimizing End-To-End At-Scale Neural Recommendation Inference
inferredcites →https://doi.org/10.1109/mc.2009.263openalex-snapshot
Matrix Factorization Techniques for Recommender Systems
inferredcites →https://doi.org/10.1109/tkde.2018.2831682openalex-snapshot
NAIS: Neural Attentive Item Similarity Model for Recommendation
inferredcites →https://doi.org/10.1145/1102351.1102441openalex-snapshot
Fast maximum margin matrix factorization for collaborative prediction
inferredcites →https://doi.org/10.1145/1401890.1401944openalex-snapshot
Factorization meets the neighborhood
inferredcites →https://doi.org/10.1145/2043932.2043990openalex-snapshot
Towards a more realistic evaluation
inferredcites →https://doi.org/10.1145/2043932.2044016openalex-snapshot
Second workshop on information heterogeneity and fusion in recommender systems (HetRec2011)
inferredcites →https://doi.org/10.1145/2507157.2507160openalex-snapshot
Evaluation of recommendations
inferredcites →https://doi.org/10.1145/2507157.2507189openalex-snapshot
Efficient top-n recommendation for very large scale binary rated datasets
inferredcites →https://doi.org/10.1145/2600428.2610382openalex-snapshot
Novelty and diversity enhancement and evaluation in recommender systems and information retrieval
inferredcites →https://doi.org/10.1145/2645710.2645746openalex-snapshot
Comparative recommender system evaluation
inferredcites →https://doi.org/10.1145/2645710.2645766openalex-snapshot
Implicit vs. explicit trust in social matrix factorization
inferredcites →https://doi.org/10.1145/2736277.2741667openalex-snapshot
A Multi-View Deep Learning Approach for Cross Domain User Modeling in Recommendation Systems
inferredcites →https://doi.org/10.1145/2766462.2767755openalex-snapshot
Image-Based Recommendations on Styles and Substitutes
inferredcites →https://doi.org/10.1145/2783258.2783346openalex-snapshot
Dynamic Matrix Factorization with Priors on Unknown Values
inferredcites →https://doi.org/10.1145/2792838.2792841openalex-snapshot
Replicable Evaluation of Recommender Systems
inferredcites →https://doi.org/10.1145/2835776.2835837openalex-snapshot
Collaborative Denoising Auto-Encoders for Top-N Recommender Systems
inferredcites →https://doi.org/10.1145/2872427.2883090openalex-snapshot
Modeling User Exposure in Recommendation
inferredcites →https://doi.org/10.1145/2911451.2911489openalex-snapshot
Fast Matrix Factorization for Online Recommendation with Implicit Feedback
inferredcites →https://doi.org/10.1145/2959100.2959134openalex-snapshot
Field-aware Factorization Machines for CTR Prediction
inferredcites →https://doi.org/10.1145/2959100.2959176openalex-snapshot
Contrasting Offline and Online Results when Evaluating Recommendation Algorithms
inferredcites →https://doi.org/10.1145/3038912.3052569openalex-snapshot
Neural Collaborative Filtering
inferredcites →https://doi.org/10.1145/3097983.3098077openalex-snapshot
Collaborative Variational Autoencoder for Recommender Systems
inferredcites →https://doi.org/10.1145/3132847.3132892openalex-snapshot
Joint Representation Learning for Top-N Recommendation with Heterogeneous Information Sources
inferredcites →https://doi.org/10.1145/3132847.3132913openalex-snapshot
Indexable Bayesian Personalized Ranking for Efficient Top-k Recommendation
inferredcites →https://doi.org/10.1145/3159652.3159687openalex-snapshot
Offline A/B Testing for Recommender Systems
inferredcites →https://doi.org/10.1145/3159652.3159688openalex-snapshot
Discrete Deep Learning for Fast Content-Aware Recommendation
inferredcites →https://doi.org/10.1145/3178876.3186146openalex-snapshot
Aesthetic-based Clothing Recommendation
inferredcites →https://doi.org/10.1145/3178876.3186150openalex-snapshot
Variational Autoencoders for Collaborative Filtering
inferredcites →https://doi.org/10.1145/3209978.3209981openalex-snapshot
Adversarial Personalized Ranking for Recommendation
inferredcites →https://doi.org/10.1145/3209978.3209991openalex-snapshot
Collaborative Memory Network for Recommendation Systems
inferredcites →https://doi.org/10.1145/3219819.3219826openalex-snapshot
Learning Tree-based Deep Model for Recommender Systems
inferredcites →https://doi.org/10.1145/3219819.3219965openalex-snapshot
Leveraging Meta-path based Context for Top- N Recommendation with A Neural Co-Attention Model
inferredcites →https://doi.org/10.1145/3219819.3220112openalex-snapshot
Local Latent Space Models for Top-N Recommendation
inferredcites →https://doi.org/10.1145/3240323.3240347openalex-snapshot
On the robustness and discriminative power of information retrieval metrics for top-N recommendation
inferredcites →https://doi.org/10.1145/3240323.3240355openalex-snapshot
Unbiased offline recommender evaluation for missing-not-at-random implicit feedback
inferredcites →https://doi.org/10.1145/3269206.3271725openalex-snapshot
Adaptive Implicit Friends Identification over Heterogeneous Network for Social Recommendation
inferredcites →https://doi.org/10.1145/3269206.3271761openalex-snapshot
Recurrent Neural Networks with Top-k Gains for Session-based Recommendations
inferredcites →https://doi.org/10.1145/3269206.3271813openalex-snapshot
An Attentive Interaction Network for Context-aware Recommendations
inferredcites →https://doi.org/10.1145/3270323.3270326openalex-snapshot
A Collective Variational Autoencoder for Top-N Recommendation with Side Information
inferredcites →https://doi.org/10.1145/3289600.3290977openalex-snapshot
Gated Attentive-Autoencoder for Content-Aware Recommendation
inferredcites →https://doi.org/10.1145/3289600.3290982openalex-snapshot
Social Attentional Memory Network
inferredcites →https://doi.org/10.1145/3298689.3346985openalex-snapshot
Personalized diffusions for top-n recommendation
inferredcites →https://doi.org/10.1145/3298689.3347036openalex-snapshot
Variational low rank multinomials for collaborative filtering with side-information
inferredcites →https://doi.org/10.1145/3298689.3347058openalex-snapshot
Are we really making much progress? A worrying analysis of recent neural recommendation approaches
inferredcites →https://doi.org/10.1145/3298689.3347069openalex-snapshot
Revisiting offline evaluation for implicit-feedback recommender systems
inferredcites →https://doi.org/10.1145/3308558.3313411openalex-snapshot
Multi-Task Feature Learning for Knowledge Graph Enhanced Recommendation
inferredcites →https://doi.org/10.1145/3308558.3313460openalex-snapshot
Signed Distance-based Deep Memory Recommender
inferredcites →https://doi.org/10.1145/3314578openalex-snapshot
Deep Item-based Collaborative Filtering for Top-N Recommendation
inferredcites →https://doi.org/10.1145/3331184.3331188openalex-snapshot
Relational Collaborative Filtering
inferredcites →https://doi.org/10.1145/3331184.3331201openalex-snapshot
Noise Contrastive Estimation for One-Class Collaborative Filtering
inferredcites →https://doi.org/10.1145/3331184.3331267openalex-snapshot
Neural Graph Collaborative Filtering
inferredcites →https://doi.org/10.1145/3336191.3371790openalex-snapshot
Distilling Structured Knowledge into Embeddings for Explainable and Accurate Recommendation
inferredcites →https://doi.org/10.1145/3340531.3411947openalex-snapshot
Multi-modal Knowledge Graphs for Recommender Systems
inferredcites →https://doi.org/10.1145/3340531.3412095openalex-snapshot
Revisiting Alternative Experimental Settings for Evaluating Top-N Item Recommendation Algorithms
inferredcites →https://doi.org/10.1145/3357384.3357924openalex-snapshot
Relation-Aware Graph Convolutional Networks for Agent-Initiated Social E-Commerce Recommendation
inferredcites →https://doi.org/10.1145/3366423.3380098openalex-snapshot
Reinforced Negative Sampling over Knowledge Graph for Recommendation
inferredcites →https://doi.org/10.1145/3366423.3380155openalex-snapshot
Mining Implicit Entity Preference from User-Item Interaction Data for Knowledge Graph Completion via Adversarial Learning
inferredcites →https://doi.org/10.1145/3372338openalex-snapshot
Improving Implicit Recommender Systems with Auxiliary Data
inferredcites →https://doi.org/10.1145/3373807openalex-snapshot
Efficient Neural Matrix Factorization without Sampling for Recommendation
inferredcites →https://doi.org/10.1145/3383313.3412226openalex-snapshot
Explainable Recommendations via Attentive Multi-Persona Collaborative Filtering
inferredcites →https://doi.org/10.1145/3383313.3412259openalex-snapshot
On Target Item Sampling in Offline Recommender System Evaluation
inferredcites →https://doi.org/10.1145/3383313.3412488openalex-snapshot
Neural Collaborative Filtering vs. Matrix Factorization Revisited
inferredcites →https://doi.org/10.1145/3383313.3412489openalex-snapshot
Are We Evaluating Rigorously? Benchmarking Recommendation for Reproducible Evaluation and Fair Comparison
inferredcites →https://doi.org/10.1145/3383313.3418479openalex-snapshot
Exploring Data Splitting Strategies for the Evaluation of Recommendation Models
inferredcites →https://doi.org/10.1145/3394486.3403226openalex-snapshot
On Sampled Metrics for Item Recommendation
inferredcites →https://doi.org/10.1145/3394486.3403253openalex-snapshot
Dual Channel Hypergraph Collaborative Filtering
inferredcites →https://doi.org/10.1145/3394486.3403254openalex-snapshot
A Framework for Recommending Accurate and Diverse Items Using Bayesian Graph Convolutional Neural Networks
inferredcites →https://doi.org/10.1145/3394486.3403262openalex-snapshot
On Sampling Top-K Recommendation Evaluation
inferredcites →https://doi.org/10.1145/3397271.3401046openalex-snapshot
How Dataset Characteristics Affect the Robustness of Collaborative Recommendation Models
inferredcites →https://doi.org/10.1145/3397271.3401096openalex-snapshot
Agreement and Disagreement between True and False-Positive Metrics in Recommender Systems Evaluation
inferredcites →https://doi.org/10.1145/3397271.3401155openalex-snapshot
Sampler Design for Implicit Feedback Data by Noisy-label Robust Learning
inferredcites →https://doi.org/10.1145/3397271.3401233openalex-snapshot
A Re-visit of the Popularity Baseline in Recommender Systems
inferredcites →https://doi.org/10.1145/3404835.3462928openalex-snapshot
Enhanced Graph Learning for Collaborative Filtering via Mutual Information Maximization
inferredcites →https://doi.org/10.1145/3404835.3463245openalex-snapshot
Elliot: A Comprehensive and Rigorous Framework for Reproducible Recommender Systems Evaluation
inferredcites →https://doi.org/10.1145/3434185openalex-snapshot
A Troubling Analysis of Reproducibility and Progress in Recommender Systems Research
inferredcites →https://doi.org/10.1145/3459637.3482016openalex-snapshot
RecBole: Towards a Unified, Comprehensive and Efficient Framework for Recommendation Algorithms
inferredcites →https://doi.org/10.1145/3564284openalex-snapshot
Bias and Debias in Recommender System: A Survey and Future Directions
inferredcites →https://doi.org/10.1145/963770.963776openalex-snapshot
Item-based top- N recommendation algorithms
inferredcites →https://doi.org/10.1609/aaai.v32i1.11866openalex-snapshot
WalkRanker: A Unified Pairwise Ranking Model With Multiple Relations for Item Recommendation
inferredcites →https://doi.org/10.1609/aaai.v33i01.330161openalex-snapshot
DeepCF: A Unified Framework of Representation Learning and Matching Function Learning in Recommender System
inferredcites →https://doi.org/10.1609/aaai.v34i01.5329openalex-snapshot
Efficient Heterogeneous Collaborative Filtering without Negative Sampling for Recommendation
inferredcites →https://doi.org/10.24963/ijcai.2017/391openalex-snapshot
MRLR: Multi-level Representation Learning for Personalized Ranking in Recommendation
inferredcites →https://doi.org/10.24963/ijcai.2017/447openalex-snapshot
Deep Matrix Factorization Models for Recommender Systems
inferredcites →https://doi.org/10.24963/ijcai.2017/485openalex-snapshot
Learning Discriminative Recommendation Systems with Side Information
inferredcites →https://doi.org/10.24963/ijcai.2018/498openalex-snapshot
Matrix completion with Preference Ranking for Top-N Recommendation
inferredcites →https://doi.org/10.24963/ijcai.2019/293openalex-snapshot
Semi-supervised User Profiling with Heterogeneous Graph Attention Networks
inferredcites →https://doi.org/10.24963/ijcai.2019/599openalex-snapshot
Quaternion Collaborative Filtering for Recommendation
inferredcites →https://doi.org/10.48550/arxiv.1507.08439openalex-snapshot
Metadata Embeddings for User and Item Cold-start Recommendations
inferredcites →https://doi.org/10.48550/arxiv.1707.07435openalex-snapshot
Deep Learning based Recommender System: A Survey and New Perspectives
inferredcites →https://doi.org/10.48550/arxiv.1902.00851openalex-snapshot
Value-aware Recommendation based on Reinforced Profit Maximization in E-commerce Systems
inferredcites →https://doi.org/10.48550/arxiv.1905.01395openalex-snapshot
On the Difficulty of Evaluating Baselines: A Study on Recommender Systems
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/978-3-031-30672-3_23openalex-snapshot
Towards Efficient and Effective Transformers for Sequential Recommendation
inferred← citeshttps://doi.org/10.1007/s10462-025-11189-8openalex-snapshot
Comparative analysis of methodologies and approaches in recommender systems utilizing large language models
inferred← citeshttps://doi.org/10.1016/j.ipm.2024.103731openalex-snapshot
Limits of predictability in top-N recommendation
inferred← citeshttps://doi.org/10.1109/cai68641.2026.11536435openalex-snapshot
Heat Learning and Rationale-Aware SSL: Boosting Recommender Systems with Residual Graph Transformers
inferred← citeshttps://doi.org/10.1109/iciss71466.2026.11715414openalex-snapshot
Comparative Evaluation of Precision and Relevance in Traditional, Graph, and LLM-Prompted Recommender Models
inferred← citeshttps://doi.org/10.1145/3539618.3591889openalex-snapshot
Towards a More User-Friendly and Easy-to-Use Benchmark Library for Recommender Systems
inferred← citeshttps://doi.org/10.1145/3604915.3608809openalex-snapshot
What We Evaluate When We Evaluate Recommender Systems: Understanding Recommender Systems’ Performance using Item Response Theory
inferred← citeshttps://doi.org/10.1145/3604915.3608820openalex-snapshot
Bootstrapped Personalized Popularity for Cold Start Recommender Systems
inferred← citeshttps://doi.org/10.1145/3604915.3609495openalex-snapshot
On Challenges of Evaluating Recommender Systems in an Offline Setting
inferred← citeshttps://doi.org/10.1145/3604915.3610643openalex-snapshot
Integrating Item Relevance in Training Loss for Sequential Recommender Systems
inferred← citeshttps://doi.org/10.1145/3604915.3610651openalex-snapshot
On the Consistency, Discriminative Power and Robustness of Sampled Metrics in Offline Top-N Recommender System Evaluation
inferred← citeshttps://doi.org/10.1145/3626772.3657732openalex-snapshot
To Search or to Recommend: Predicting Open-App Motivation with Neural Hawkes Process
inferred← citeshttps://doi.org/10.1145/3629170openalex-snapshot
Exploring the Landscape of Recommender Systems Evaluation: Practices and Perspectives
inferred← citeshttps://doi.org/10.1145/3637528.3671655openalex-snapshot
From Variability to Stability: Advancing RecSys Benchmarking Practices
inferred← citeshttps://doi.org/10.1145/3640457.3688195openalex-snapshot
Does It Look Sequential? An Analysis of Datasets for Evaluation of Sequential Recommendations
inferred← citeshttps://doi.org/10.1145/3666088openalex-snapshot
Adversarial Item Promotion on Visually-Aware Recommender Systems by Guided Diffusion
inferred← citeshttps://doi.org/10.1145/3675163openalex-snapshot
Our Model Achieves Excellent Performance on MovieLens: What Does It Mean?
inferred← citeshttps://doi.org/10.1145/3690624.3709214openalex-snapshot
Enhancing Graph Contrastive Learning with Reliable and Informative Augmentation for Recommendation
inferred← citeshttps://doi.org/10.1145/3701716.3715213openalex-snapshot
Comment Staytime Prediction with LLM-enhanced Comment Understanding
inferred← citeshttps://doi.org/10.1145/3705328.3748164openalex-snapshot
Time to Split: Exploring Data Splitting Strategies for Offline Evaluation of Sequential Recommenders
inferred← citeshttps://doi.org/10.1145/3705328.3759329openalex-snapshot
Don't Get Ahead of Yourself: A Critical Study on Data Leakage in Offline Evaluation of Sequential Recommenders
inferred← citeshttps://doi.org/10.1145/3711896.3736979openalex-snapshot
Generating Long Semantic IDs in Parallel for Recommendation
inferred← citeshttps://doi.org/10.1145/3711896.3737051openalex-snapshot
MockLLM: A Multi-Agent Behavior Collaboration Framework for Online Job Seeking and Recruiting
inferred← citeshttps://doi.org/10.1145/3728373openalex-snapshot
Recall, Robustness, and Lexicographic Evaluation
inferred← citeshttps://doi.org/10.1145/3773078.3841280openalex-snapshot
Your 5-Core Train Split May Not Be 5-Core: Core Filtering and Temporal Splitting Do Not Commute
inferred← citeshttps://doi.org/10.1145/3774904.3792156openalex-snapshot
DiffGRM: Diffusion-based Generative Recommendation Model
inferred← citeshttps://doi.org/10.1145/3787969openalex-snapshot
An Analysis of Sequential Patterns in Datasets for Evaluation of Sequential Recommendations
inferred← citeshttps://doi.org/10.32657/10356/173690openalex-snapshot
Impact of temporal context on recommender systems along global timeline
inferred← citeshttps://doi.org/10.3390/e24111639openalex-snapshot
Time-Aware Explainable Recommendation via Updating Enabled Online Prediction
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