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},
}