Papers with Code 아카이브

Collaborative Filtering

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평가표

4

보존된 평가 기록

30

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/sunwardtree/lt-hgcf

공식 코드

A Light Heterogeneous Graph Collaborative Filtering Model using Textual Information

https://github.com/sustechbruce/restc-source-code

공식 코드

Spatio-Temporal Contrastive Learning Enhanced GNNs for Session-based Recommendation

https://github.com/tanatosuu/gde

공식 코드

Less is More: Reweighting Important Spectral Graph Features for Recommendation

https://github.com/tanatosuu/sgfcf

공식 코드

How Powerful is Graph Filtering for Recommendation

https://github.com/tebesu/CollaborativeMemoryNetwork

공식 코드

Collaborative Memory Network for Recommendation Systems

https://github.com/thu-ml/CF-UIcA

공식 코드

Collaborative Filtering with User-Item Co-Autoregressive Models

https://github.com/thudm/recdcl

공식 코드

RecDCL: Dual Contrastive Learning for Recommendation

https://github.com/thuwangcy/directau

공식 코드

Towards Representation Alignment and Uniformity in Collaborative Filtering

https://github.com/tienmt/UQMC

공식 코드

Simulation comparisons between Bayesian and de-biased estimators in low-rank matrix completion

https://github.com/tingruew/diffusionmodels-in-recsys

공식 코드

Diffusion Models in Recommendation Systems: A Survey

https://github.com/tjtp/kdar

공식 코드

Knowledge-aware Dual-side Attribute-enhanced Recommendation

https://github.com/ton-moy/surprise-and-serendipity

공식 코드

Topic-Level Bayesian Surprise and Serendipity for Recommender Systems

https://github.com/tonyrivermsfly/TSPRA

공식 코드

Unifying Topic, Sentiment & Preference in an HDP-Based Rating Regression Model for Online Reviews

https://github.com/trantin84/wigcn

공식 코드

Improvement Graph Convolution Collaborative Filtering with Weighted addition input

https://github.com/tsinghua-fib-lab/Causal-Recommender-Systems

공식 코드

Causal Inference in Recommender Systems: A Survey and Future Directions

https://github.com/tsinghua-fib-lab/DGCN

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DGCN: Diversified Recommendation with Graph Convolutional Networks

https://github.com/tuyki/mogp-decomposition

공식 코드

Multi-output Gaussian Processes for Uncertainty-aware Recommender Systems

https://github.com/u-rara/afdgcf

공식 코드

AFDGCF: Adaptive Feature De-correlation Graph Collaborative Filtering for Recommendations

https://github.com/udellgroup/oboe

공식 코드

OBOE: Collaborative Filtering for AutoML Model Selection

https://github.com/unitdan/ipl

공식 코드

Popularity Debiasing from Exposure to Interaction in Collaborative Filtering

https://github.com/user683/hnlmrec

공식 코드

Can LLM-Driven Hard Negative Sampling Empower Collaborative Filtering? Findings and Potentials

https://github.com/usydnlp/Glocal_K

공식 코드

GLocal-K: Global and Local Kernels for Recommender Systems

https://github.com/vectorinstitute/recommender-systems-survey

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A Comprehensive Review of Recommender Systems: Transitioning from Theory to Practice

https://github.com/weiyinwei/kgcr

공식 코드

Causal Inference for Knowledge Graph based Recommendation

https://github.com/wenqifan03/gtn-sigir2022

공식 코드

Graph Trend Filtering Networks for Recommendations

https://github.com/wings236/pogcn

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Multi-Behavior Collaborative Filtering with Partial Order Graph Convolutional Networks

https://github.com/wonbinkweon/dre_www2020

공식 코드

Deep Rating Elicitation for New Users in Collaborative Filtering

https://github.com/wqxleo/kcf-plm

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Knowledge-aware Collaborative Filtering with Pre-trained Language Model for Personalized Review-based Rating Prediction

https://github.com/wu-xi/dins

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Dimension Independent Mixup for Hard Negative Sample in Collaborative Filtering

https://github.com/wu1hong/sccf

공식 코드

Unifying Graph Convolution and Contrastive Learning in Collaborative Filtering

https://github.com/wujcan/GCM

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Graph Convolution Machine for Context-aware Recommender System

https://github.com/wujcan/SGL

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Self-supervised Graph Learning for Recommendation

https://github.com/wuliwei9278/SQL-Rank

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Advances in Collaborative Filtering and Ranking

https://github.com/xhcdream/kcgn

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Knowledge-aware Coupled Graph Neural Network for Social Recommendation

https://github.com/xiangning-chen/SIF

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Efficient Neural Interaction Function Search for Collaborative Filtering

https://github.com/xiangwang1223/disentangled_graph_collaborative_filtering

공식 코드

Disentangled Graph Collaborative Filtering

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.