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Block-Aware Item Similarity Models for Top- N Recommendation
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-1-4899-7637-6openalex-snapshot
Recommender Systems Handbook
inferredcites →https://doi.org/10.1007/978-3-642-33786-4_26openalex-snapshot
Robust and Efficient Subspace Segmentation via Least Squares Regression
inferredcites →https://doi.org/10.1016/s0167-6377(99)00074-7openalex-snapshot
On the convergence of the block nonlinear Gauss–Seidel method under convex constraints
inferredcites →https://doi.org/10.1073/pnas.35.11.652openalex-snapshot
On a Theorem of Weyl Concerning Eigenvalues of Linear Transformations I
inferredcites →https://doi.org/10.1109/cvpr.2014.482openalex-snapshot
Robust Subspace Segmentation with Block-Diagonal Prior
inferredcites →https://doi.org/10.1109/iccv.2015.486openalex-snapshot
Learning Image and User Features for Recommendation in Social Networks
inferredcites →https://doi.org/10.1109/icdm.2005.14openalex-snapshot
A Scalable Collaborative Filtering Framework Based on Co-Clustering
inferredcites →https://doi.org/10.1109/icdm.2008.22openalex-snapshot
Collaborative Filtering for Implicit Feedback Datasets
inferredcites →https://doi.org/10.1109/icdm.2008.57openalex-snapshot
Non-negative Matrix Factorization on Manifold
inferredcites →https://doi.org/10.1109/icdm.2011.134openalex-snapshot
SLIM: Sparse Linear Methods for Top-N Recommender Systems
inferredcites →https://doi.org/10.1109/icdm.2014.112openalex-snapshot
LorSLIM: Low Rank Sparse Linear Methods for Top-N Recommendations
inferredcites →https://doi.org/10.1109/tip.2017.2655449openalex-snapshot
Effective Multi-Query Expansions: Collaborative Deep Networks for Robust Landmark Retrieval
inferredcites →https://doi.org/10.1109/tip.2017.2764262openalex-snapshot
Implicit Block Diagonal Low-Rank Representation
inferredcites →https://doi.org/10.1109/tkde.2018.2830336openalex-snapshot
Efficient Mining of Frequent Patterns on Uncertain Graphs
inferredcites →https://doi.org/10.1109/tkde.2018.2831682openalex-snapshot
NAIS: Neural Attentive Item Similarity Model for Recommendation
inferredcites →https://doi.org/10.1109/tpami.2018.2794348openalex-snapshot
Subspace Clustering by Block Diagonal Representation
inferredcites →https://doi.org/10.1137/1.9781611974348.15openalex-snapshot
Top-N Recommendation with Novel Rank Approximation
inferredcites →https://doi.org/10.1145/1060745.1060754openalex-snapshot
Improving recommendation lists through topic diversification
inferredcites →https://doi.org/10.1145/1076034.1076056openalex-snapshot
Scalable collaborative filtering using cluster-based smoothing
inferredcites →https://doi.org/10.1145/1401890.1401944openalex-snapshot
Factorization meets the neighborhood
inferredcites →https://doi.org/10.1145/1454008.1454031openalex-snapshot
A random walk method for alleviating the sparsity problem in collaborative filtering
inferredcites →https://doi.org/10.1145/1864708.1864721openalex-snapshot
Performance of recommender algorithms on top-n recommendation tasks
inferredcites →https://doi.org/10.1145/2187836.2187840openalex-snapshot
An exploration of improving collaborative recommender systems via user-item subgroups
inferredcites →https://doi.org/10.1145/2365952.2365983openalex-snapshot
Sparse linear methods with side information for top-n recommendations
inferredcites →https://doi.org/10.1145/2488388.2488520openalex-snapshot
Localized matrix factorization for recommendation based on matrix block diagonal forms
inferredcites →https://doi.org/10.1145/2507157.2507163openalex-snapshot
Hidden factors and hidden topics
inferredcites →https://doi.org/10.1145/2736277openalex-snapshot
Proceedings of the 24th International Conference on World Wide Web - WWW '15
inferredcites →https://doi.org/10.1145/2835776.2835837openalex-snapshot
Collaborative Denoising Auto-Encoders for Top-N Recommender Systems
inferredcites →https://doi.org/10.1145/2911451.2911489openalex-snapshot
Fast Matrix Factorization for Online Recommendation with Implicit Feedback
inferredcites →https://doi.org/10.1145/2959100.2959185openalex-snapshot
Local Item-Item Models For Top-N Recommendation
inferredcites →https://doi.org/10.1145/2983323.2983649openalex-snapshot
Top-N Recommendation on Graphs
inferredcites →https://doi.org/10.1145/3038912.3052569openalex-snapshot
Neural Collaborative Filtering
inferredcites →https://doi.org/10.1145/3038912.3052694openalex-snapshot
A Generic Coordinate Descent Framework for Learning from Implicit Feedback
inferredcites →https://doi.org/10.1145/3077136.3080697openalex-snapshot
Top-N Recommendation with High-Dimensional Side Information via Locality Preserving Projection
inferredcites →https://doi.org/10.1145/3178876.3186150openalex-snapshot
Variational Autoencoders for Collaborative Filtering
inferredcites →https://doi.org/10.1145/3184558.3191586openalex-snapshot
Dynamic Local Models for Online Recommendation
inferredcites →https://doi.org/10.1145/3209978.3209991openalex-snapshot
Collaborative Memory Network for Recommendation Systems
inferredcites →https://doi.org/10.1145/3219819.3220112openalex-snapshot
Local Latent Space Models for Top-N Recommendation
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/10.1145/3308558.3313710openalex-snapshot
Embarrassingly Shallow Autoencoders for Sparse Data
inferredcites →https://doi.org/10.1145/3314578openalex-snapshot
Deep Item-based Collaborative Filtering for Top-N Recommendation
inferredcites →https://doi.org/10.1145/3331184.3331196openalex-snapshot
Bayesian Personalized Feature Interaction Selection for Factorization Machines
inferredcites →https://doi.org/10.1145/3372154openalex-snapshot
Local Variational Feature-Based Similarity Models for Recommending Top- N New Items
inferredcites →https://doi.org/10.1145/371920.372071openalex-snapshot
Item-based collaborative filtering recommendation algorithms
inferredcites →https://doi.org/10.1145/963770.963776openalex-snapshot
Item-based top- N recommendation algorithms
inferredcites →https://doi.org/10.52202/085713openalex-snapshot
Advances in Neural Information Processing Systems 19
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/978-3-032-21324-2_9openalex-snapshot
A Reproducible and Fair Evaluation of Partition-Aware Collaborative Filtering
inferred← citeshttps://doi.org/10.1016/j.inffus.2023.101862openalex-snapshot
Dual-interactive fusion for code-mixed deep representation learning in tag recommendation
inferred← citeshttps://doi.org/10.1109/tkde.2024.3418080openalex-snapshot
FPSR+: Toward Robust, Efficient, and Scalable Collaborative Filtering With Partition-Aware Item Similarity Modeling
inferred← citeshttps://doi.org/10.1145/3442381.3450038openalex-snapshot
Leveraging Review Properties for Effective Recommendation
inferred← citeshttps://doi.org/10.1145/3460231.3474247openalex-snapshot
Pessimistic Reward Models for Off-Policy Learning in Recommendation
inferred← citeshttps://doi.org/10.1145/3466641openalex-snapshot
Multi-Graph Heterogeneous Interaction Fusion for Social Recommendation
inferred← citeshttps://doi.org/10.1145/3467023openalex-snapshot
Collaborative Reflection-Augmented Autoencoder Network for Recommender Systems
inferred← citeshttps://doi.org/10.1145/3483611openalex-snapshot
An Unsupervised Aspect-Aware Recommendation Model with Explanation Text Generation
inferred← citeshttps://doi.org/10.1145/3485447.3512072openalex-snapshot
Off-policy Learning over Heterogeneous Information for Recommendation
inferred← citeshttps://doi.org/10.1145/3490181openalex-snapshot
Reinforced Neighborhood Selection Guided Multi-Relational Graph Neural Networks
inferred← citeshttps://doi.org/10.1145/3512767openalex-snapshot
Reinforcement Routing on Proximity Graph for Efficient Recommendation
inferred← citeshttps://doi.org/10.1145/3543507.3583240openalex-snapshot
Fine-tuning Partition-aware Item Similarities for Efficient and Scalable Recommendation
inferred← citeshttps://doi.org/10.1145/3544105openalex-snapshot
Adversarial Auto-encoder Domain Adaptation for Cold-start Recommendation with Positive and Negative Hypergraphs
inferred← citeshttps://doi.org/10.1145/3555373openalex-snapshot
Personal or General? A Hybrid Strategy with Multi-factors for News Recommendation
inferred← citeshttps://doi.org/10.1145/3568029openalex-snapshot
Pessimistic Decision-Making for Recommender Systems
inferred← citeshttps://doi.org/10.1145/3611385openalex-snapshot
SLED: Structure Learning based Denoising for Recommendation
inferred← citeshttps://doi.org/10.1145/3746637openalex-snapshot
Cold-start User Recommendation via Heterogeneous Domain Adaptation
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