This is the code for the KDD 2018 paper: STAMP: Short-Term Attention/Memory Priority Model for Session-based Recommendation. We have implemented our methods in Tensorflow.
These are two datasets we used in our paper. After download them, you can put them in the folder datas\, then process them by process_rsc.py and process_cikm.py respectively.
YOOCHOOSE: http://2015.recsyschallenge.com/challenge.html
DIGINETICA: http://cikm2016.cs.iupui.edu/cikm-cup
Beacuse for each dataset we have some different parameters, there are two model files STAMP_rsc.py and STAMP_cikm.py.
So you run the filecmain.py to train the model.
For example: python3 cmain.py -m stamp_rsc -d rsc15_64 -n and python3 cmain.py -m stamp_cikm -d cikm16 -n
Or you can run it by using the run.sh directly.
. Python 3 . Tensorflow 1.4
Please cite our papaer:
@inproceedings{Liu18STAMP,
author = {Liu, Qiao and Zeng, Yifu and Mokhosi, Refuoe and Zhang, Haibin},
title = {STAMP: Short-Term Attention/Memory Priority Model for Session-based Recommendation},
booktitle = {Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery \&\#38; Data Mining},
year = {2018},
location = {London, United Kingdom},
pages = {1831--1839},
}