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cf-kan_aaai's Introduction

CF-KAN

KAN (Kolmogorov-Arnold Network)-based Collaborative Filtering (CF)

overview_v2

CF-KAN is a recommendation method (collaborative filtering) based on the Kolmogorov-Arnold Network (KAN, https://arxiv.org/abs/2404.19756) approach. This project leverages and explores the power of KAN for CF-based recommendation.

Running

To get started with CF-KAN, clone the repository and install the required dependencies (pytorch and numpy, etc)

If you are ready, test it with

python main.py

The Results (Recommendation Accuracy)

We comprehensively compare CF-KAN with the following categories of recommendation models: Matrix factorization-based methods: MF-BPR, NeuMF, and DMF; Autoencoder-based methods: CDAE, Multi-DAE, and RecVAE; GCN-based methods: SpectralCF, NGCF ,LightGCN, SGL, and NCL; Generative model-based methods: CFGAN, RecVAE, and DiffRec.

Method ML-1M Yelp Anime
R@10 R@20 N@10 N@20 R@10 R@20 N@10 N@20 R@10 R@20 N@10 N@20
MF-BPR 0.0876 0.1503 0.0749 0.0966 0.0341 0.0560 0.0210 0.0341 0.1521 0.2449 0.2925 0.3153
NeuMF 0.0845 0.1465 0.0759 0.0965 0.0378 0.0637 0.0230 0.0308 0.1531 0.2442 0.3277 0.3259
DMF 0.0799 0.1368 0.0731 0.0921 0.0342 0.0588 0.0208 0.0282 0.1386 0.2161 0.3277 0.3122
CDAE 0.0991 0.1705 0.0829 0.1078 0.0444 0.0703 0.0280 0.0360 0.2031 0.2845 0.4652 0.4301
MultiDAE 0.0975 0.1707 0.0820 0.1046 0.0531 0.0876 0.0316 0.0421 0.2022 0.2882 0.4577 0.4125
RecVAE 0.0835 0.1422 0.0769 0.0963 0.0493 0.0824 0.0303 0.0403 0.2137 0.3068 0.4105 0.4068
SpectralCF 0.0751 0.1291 0.0740 0.0909 0.0368 0.0572 0.0201 0.0298 0.1633 0.2564 0.3102 0.3236
NGCF 0.0864 0.1484 0.0805 0.1038 0.0417 0.0708 0.0255 0.0346 0.2071 0.3043 0.3937 0.3827
LightGCN 0.0824 0.1419 0.0793 0.1006 0.0505 0.0858 0.0312 0.0417 0.2071 0.3043 0.3937 0.3827
SGL 0.0885 0.1575 0.0802 0.1029 0.0564 0.0944 0.0346 0.0462 0.1994 0.2918 0.3748 0.3652
NCL 0.0878 0.1471 0.0819 0.1011 0.0535 0.0906 0.0326 0.0438 0.2063 0.3047 0.3919 0.3819
CFGAN 0.0684 0.1181 0.0663 0.0828 0.0206 0.0347 0.0129 0.0172 0.1946 0.2889 0.4601 0.4289
DiffRec 0.1021 0.1763 0.0877 0.1131 0.0554 0.0914 0.0345 0.0452 0.2104 0.3012 0.5047 0.4649
CF-KAN 0.1065 0.1831 0.0894 0.1152 0.0590 0.0961 0.0359 0.0471 0.2287 0.3261 0.5256 0.4875

Etc.

For the implementation of KANs, I've referred to the following repos: EfficentKAN, Visualization API

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