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implementation for the paper "FISM: Factored Item Similarity Models for Top-N Recommender Systems" by Tensorflow 1.2

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FISM

This repository contains an implementation for the paper "FISM: Factored Item Similarity Models for Top-N Recommender Systems" by Tensorflow 1.2.

Requirement

Python 3.5

Tensorflow 1.2

Dataset

This data set is extracted from movielens-1m by Dr. Xiangnan He. The data set is first proposed by the paper "Neural Collaborative Filtering".

Evaluation

I use the hit ratio(aka HR) metric to evalute the model performance. I tune the hyperparameter carefully for the best performance. Specifically, the best HR this code can achieve is 71.05%, after about 5 epoches training.

Citation

If you use the codes for your paper as baseline implementation, please cite the link: "https://github.com/yushuai/FISM"

Last update date

2018/1/15

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implementation for the paper "FISM: Factored Item Similarity Models for Top-N Recommender Systems" by Tensorflow 1.2

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