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Collaborative Filtering

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평가표

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보존된 평가 기록

30

코드

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

https://github.com/kuandeng/LightGCN

공식 코드

LightGCN: Simplifying and Powering Graph Convolution Network for Recommendation

https://github.com/kylokano/LatentCRS

공식 코드

Harmonizing Large Language Models with Collaborative Behavioral Signals for Conversational Recommendation

https://github.com/lasigeBioTM/ChemRecSys

공식 코드

Hybrid Semantic Recommender System for Chemical Compounds

https://github.com/learning-layers/TagRec

공식 코드

Attention Please! A Hybrid Resource Recommender Mimicking Attention-Interpretation Dynamics

https://github.com/lehengthu/advinfonce

공식 코드

Empowering Collaborative Filtering with Principled Adversarial Contrastive Loss

https://github.com/lehengthu/alpharec

공식 코드

Language Representations Can be What Recommenders Need: Findings and Potentials

https://github.com/lenskit/lkpy

공식 코드

LensKit for Python: Next-Generation Software for Recommender System Experiments

https://github.com/leolouis14/kucnet

공식 코드

Knowledge-Enhanced Recommendation with User-Centric Subgraph Network

https://github.com/linxyhaha/tdro

공식 코드

Temporally and Distributionally Robust Optimization for Cold-Start Recommendation

https://github.com/linzh92/DeepICF

공식 코드

Deep Item-based Collaborative Filtering for Top-N Recommendation

https://github.com/liubin06/BCL

공식 코드

Bayesian Negative Sampling for Recommendation

https://github.com/liubin06/dpl

공식 코드

Debiased Pairwise Learning from Positive-Unlabeled Implicit Feedback

https://github.com/liubin06/variationalbpr

공식 코드

Variational Bayesian Personalized Ranking

https://github.com/liufancs/fla

공식 코드

Feature-level Attentive ICF for Recommendation

https://github.com/liuqidong07/LLMEmb

공식 코드

LLMEmb: Large Language Model Can Be a Good Embedding Generator for Sequential Recommendation

https://github.com/lmcRS/AWS-recommendation-papers

공식 코드

A Survey on Accuracy-oriented Neural Recommendation: From Collaborative Filtering to Information-rich Recommendation

https://github.com/lukezane118/hgch

공식 코드

HGCH: A Hyperbolic Graph Convolution Network Model for Heterogeneous Collaborative Graph Recommendation

https://github.com/luoxiao12/CHCF

공식 코드

Criterion-based Heterogeneous Collaborative Filtering for Multi-behavior Implicit Recommendation

https://github.com/lzheng21/SpectralCF

공식 코드

Spectral Collaborative Filtering

https://github.com/magronp/ncacf

공식 코드

Neural content-aware collaborative filtering for cold-start music recommendation

https://github.com/makgyver/pyros

공식 코드

Exploiting sparsity to build efficient kernel based collaborative filtering for top-N item recommendation

https://github.com/makgyver/rectorch

공식 코드

Conditioned Variational Autoencoder for top-N item recommendation

https://github.com/malajikuai/tdsgl

공식 코드

Topology-aware Debiased Self-supervised Graph Learning for Recommendation

https://github.com/mangaki/balse

공식 코드

Using Posters to Recommend Anime and Mangas in a Cold-Start Scenario

https://github.com/marlin-codes/HICF

공식 코드

HICF: Hyperbolic Informative Collaborative Filtering

https://github.com/marlin-codes/HRCF

공식 코드

HRCF: Enhancing Collaborative Filtering via Hyperbolic Geometric Regularization

https://github.com/mbhynes/als-ncg

공식 코드

Algorithmic Acceleration of Parallel ALS for Collaborative Filtering: Speeding up Distributed Big Data Recommendation in Spark

https://github.com/meicrs/gdsrec

공식 코드

GDSRec: Graph-Based Decentralized Collaborative Filtering for Social Recommendation

https://github.com/mgulcin/FastTextRec

공식 코드

Utilizing FastText for Venue Recommendation

https://github.com/mgulcin/mmcl

공식 코드

Multi-Margin Cosine Loss: Proposal and Application in Recommender Systems

https://github.com/miaomiao-cai2/kdd2024-paac

공식 코드

Popularity-Aware Alignment and Contrast for Mitigating Popularity Bias

https://github.com/mohit-shrma/matfac

공식 코드

Adaptive Matrix Completion for the Users and the Items in Tail

https://github.com/mravanba/deep_exchangeable_tensors

공식 코드

Deep Models of Interactions Across Sets

https://github.com/mtics/feddae

공식 코드

Personalized Federated Collaborative Filtering: A Variational AutoEncoder Approach

https://github.com/mylove-xab/kddcupfinal

공식 코드

Text-Driven Neural Collaborative Filtering Model for Paper Source Tracing

https://github.com/nemexur/revisit-bpr

공식 코드

Revisiting BPR: A Replicability Study of a Common Recommender System Baseline

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