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Graph-based Regularization on Embedding Layers for 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/10.1007/978-3-540-45167-9_12openalex-snapshot
Kernels and Regularization on Graphs
inferredcites →https://doi.org/10.1007/978-3-642-13287-2openalex-snapshot
Music Recommendation and Discovery
inferredcites →https://doi.org/10.1109/icdm.2008.16openalex-snapshot
One-Class Collaborative Filtering
inferredcites →https://doi.org/10.1109/icdm.2018.00035openalex-snapshot
Self-Attentive Sequential Recommendation
inferredcites →https://doi.org/10.1109/jstsp.2017.2726975openalex-snapshot
Graph Learning From Data Under Laplacian and Structural Constraints
inferredcites →https://doi.org/10.1109/mc.2009.263openalex-snapshot
Matrix Factorization Techniques for Recommender Systems
inferredcites →https://doi.org/10.1109/mic.2003.1167344openalex-snapshot
Amazon.com recommendations: item-to-item collaborative filtering
inferredcites →https://doi.org/10.1109/tkde.2018.2833443openalex-snapshot
Heterogeneous Information Network Embedding for Recommendation
inferredcites →https://doi.org/10.1145/1390156openalex-snapshot
Proceedings of the 25th international conference on Machine learning - ICML '08
inferredcites →https://doi.org/10.1145/1390681.1390696openalex-snapshot
Model Selection Through Sparse Maximum Likelihood Estimation for Multivariate Gaussian or Binary Data
inferredcites →https://doi.org/10.1145/1935826.1935877openalex-snapshot
Recommender systems with social regularization
inferredcites →https://doi.org/10.1145/215206openalex-snapshot
Proceedings of the 18th annual international ACM SIGIR conference on Research and development in information retrieval - SIGIR '95
inferredcites →https://doi.org/10.1145/2556195.2556259openalex-snapshot
Personalized entity recommendation
inferredcites →https://doi.org/10.1145/2792838.2799671openalex-snapshot
Top-N Recommendation with Missing Implicit Feedback
inferredcites →https://doi.org/10.1145/2806416.2806528openalex-snapshot
Semantic Path based Personalized Recommendation on Weighted Heterogeneous Information Networks
inferredcites →https://doi.org/10.1145/2835776.2835837openalex-snapshot
Collaborative Denoising Auto-Encoders for Top-N Recommender Systems
inferredcites →https://doi.org/10.1145/2911451.2914683openalex-snapshot
A Dynamic Recurrent Model for Next Basket Recommendation
inferredcites →https://doi.org/10.1145/2939672.2939673openalex-snapshot
Collaborative Knowledge Base Embedding for Recommender Systems
inferredcites →https://doi.org/10.1145/2959100.2959190openalex-snapshot
Deep Neural Networks for YouTube Recommendations
inferredcites →https://doi.org/10.1145/3038912.3052569openalex-snapshot
Neural Collaborative Filtering
inferredcites →https://doi.org/10.1145/3052769openalex-snapshot
Improving the Quality of Recommendations for Users and Items in the Tail of Distribution
inferredcites →https://doi.org/10.1145/3097983.3098063openalex-snapshot
Meta-Graph Based Recommendation Fusion over Heterogeneous Information Networks
inferredcites →https://doi.org/10.1145/3109859.3109882openalex-snapshot
Translation-based Recommendation
inferredcites →https://doi.org/10.1145/3132847.3132926openalex-snapshot
Neural Attentive Session-based Recommendation
inferredcites →https://doi.org/10.1145/3159652.3159656openalex-snapshot
Personalized Top-N Sequential Recommendation via Convolutional Sequence Embedding
inferredcites →https://doi.org/10.1145/3159652.3159710openalex-snapshot
A Path-constrained Framework for Discriminating Substitutable and Complementary Products in E-commerce
inferredcites →https://doi.org/10.1145/3178876.3186150openalex-snapshot
Variational Autoencoders for Collaborative Filtering
inferredcites →https://doi.org/10.1145/3219819.3219826openalex-snapshot
Learning Tree-based Deep Model for Recommender Systems
inferredcites →https://doi.org/10.1145/3219819.3219890openalex-snapshot
Graph Convolutional Neural Networks for Web-Scale Recommender Systems
inferredcites →https://doi.org/10.1145/3234944.3234956openalex-snapshot
Attentive Contextual Denoising Autoencoder for Recommendation
inferredcites →https://doi.org/10.1145/3269206.3271730openalex-snapshot
Regularizing Matrix Factorization with User and Item Embeddings for 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/10.1145/3289600.3290975openalex-snapshot
A Simple Convolutional Generative Network for Next Item Recommendation
inferredcites →https://doi.org/10.1145/3292500.3330956openalex-snapshot
Stability and Generalization of Graph Convolutional Neural Networks
inferredcites →https://doi.org/10.1145/3308558.3313411openalex-snapshot
Multi-Task Feature Learning for Knowledge Graph Enhanced Recommendation
inferredcites →https://doi.org/10.1145/3308558.3313417openalex-snapshot
Knowledge Graph Convolutional Networks for Recommender Systems
inferredcites →https://doi.org/10.1145/3308558.3313488openalex-snapshot
Graph Neural Networks for Social Recommendation
inferredcites →https://doi.org/10.1145/3308558.3313493openalex-snapshot
Collaborative Similarity Embedding for Recommender Systems
inferredcites →https://doi.org/10.1145/3312738openalex-snapshot
Exploring High-Order User Preference on the Knowledge Graph for Recommender Systems
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/10.1145/3331184.3331267openalex-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/10.1162/neco.1995.7.1.108openalex-snapshot
Training with Noise is Equivalent to Tikhonov Regularization
inferredcites →https://doi.org/10.1214/aoms/1177697089openalex-snapshot
A Correspondence Between Bayesian Estimation on Stochastic Processes and Smoothing by Splines
inferredcites →https://doi.org/10.1609/aaai.v33i01.3301346openalex-snapshot
Session-Based Recommendation with Graph Neural Networks
inferredcites →https://doi.org/10.18653/v1/d19-1670openalex-snapshot
EDA: Easy Data Augmentation Techniques for Boosting Performance on Text Classification Tasks
inferredcites →https://doi.org/10.24963/ijcai.2017/511openalex-snapshot
Exploiting Music Play Sequence for Music Recommendation
inferredcites →https://doi.org/10.48550/arxiv.1706.02263openalex-snapshot
Graph Convolutional Matrix Completion
inferredcites →https://doi.org/10.7551/mitpress/3206.001.0001openalex-snapshot
Gaussian Processes for Machine Learning
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/978-3-031-09917-5_3openalex-snapshot
Multilevel Feature Interaction Learning for Session-Based Recommendation via Graph Neural Networks
inferred← citeshttps://doi.org/10.1007/978-3-031-21689-3_1openalex-snapshot
A Sequential Recommender System with Embeddings Based on GraphSage Aggregators
inferred← citeshttps://doi.org/10.1007/978-981-19-8152-4_11openalex-snapshot
Regularized Framework on Heterogeneous Hypergraph Model for Personal Recommendation
inferred← citeshttps://doi.org/10.1021/acsami.3c11790openalex-snapshot
MOF-GRU: A MOFid-Aided Deep Learning Model for Predicting the Gas Separation Performance of Metal–Organic Frameworks
inferred← citeshttps://doi.org/10.1080/01621459.2025.2547978openalex-snapshot
Word-Level Maximum Mean Discrepancy Regularization for Word Embedding
inferred← citeshttps://doi.org/10.1088/1742-6596/1717/1/012002openalex-snapshot
Research Problems in Recommender systems
inferred← citeshttps://doi.org/10.1093/bib/bbad410openalex-snapshot
A comprehensive review and evaluation of graph neural networks for non-coding RNA and complex disease associations
inferred← citeshttps://doi.org/10.1109/access.2021.3096609openalex-snapshot
Graph Convolutional Embeddings for Recommender Systems
inferred← citeshttps://doi.org/10.1109/ispa63168.2024.00217openalex-snapshot
AutoMP: A Tool to Automate Performance Testing for Model Placement on GPUs
inferred← citeshttps://doi.org/10.1109/tbdata.2024.3460534openalex-snapshot
Dynamic NN-Descent: An Efficient k-NN Graph Construction Method
inferred← citeshttps://doi.org/10.1109/tetc.2023.3292866openalex-snapshot
A Graph-Incorporated Latent Factor Analysis Model for High-Dimensional and Sparse Data
inferred← citeshttps://doi.org/10.1145/3511019openalex-snapshot
KR-GCN: Knowledge-Aware Reasoning with Graph Convolution Network for Explainable Recommendation
inferred← citeshttps://doi.org/10.1145/3511896openalex-snapshot
Who will Win the Data Science Competition? Insights from KDD Cup 2019 and Beyond
inferred← citeshttps://doi.org/10.1145/3527662openalex-snapshot
Knowledge-Enhanced Attributed Multi-Task Learning for Medicine Recommendation
inferred← citeshttps://doi.org/10.1145/3535101openalex-snapshot
Graph Neural Networks in Recommender Systems: A Survey
inferred← citeshttps://doi.org/10.1145/3611385openalex-snapshot
SLED: Structure Learning based Denoising for Recommendation
inferred← citeshttps://doi.org/10.1145/3616855.3635787openalex-snapshot
Collaboration and Transition: Distilling Item Transitions into Multi-Query Self-Attention for Sequential Recommendation
inferred← citeshttps://doi.org/10.1145/3648612openalex-snapshot
Improving Semi-Supervised Text Classification with Dual Meta-Learning
inferred← citeshttps://doi.org/10.1145/3726302.3730320openalex-snapshot
D ata R ec : A Python Library for Standardized and Reproducible Data Management in Recommender Systems
inferred← citeshttps://doi.org/10.1145/3770855.3818208openalex-snapshot
Purify and Generalize: Efficient Dual-End Adapters for Sequential Recommendation
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