TEA: A Sequential Recommendation Framework via Temporally Evolving Aggregations

Last update: Oct 16, 2022

Related tags

Deep Learning TEA

Overview

TEA: A Sequential Recommendation Framework via Temporally Evolving Aggregations

Requirements

python 3.6
torch 1.9
numpy 1.19

Quick Start

The experiment uses the Yelp and Epinions data sets. Data preprocessing is required before training. Here uses yelp as an example

python my_preprocess_yelp.py

TEA can be trained afterwards

python run_gatmeta_tea_gat_yelp.py #TEA-A
python run_gatmeta_tea_gsage_yelp.py #TEA-S

The training method of the baseline in the paper is similar

Experiment Result

Epinions

Yelp

Owner

DMIRLAB

DMIRLAB Public Repository

GitHub Repository

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