A pytorch and tensorflow GPU implementation of ALSTP.
Yangyang Guo, Zhiyong Cheng, Liqiang Nie, Yinglong Wang, Junma and Mohan Kankanhalli (2018). Attentive Long Short-Term Preference Modeling for Personalized Product Search. In TOIS.
Please cite our TOIS paper if you use our codes. Thanks!
You can download the Amazon Dataset from http://jmcauley.ucsd.edu/data/amazon.
-
python==3.6
-
pandas==0.24.2
-
numpy==1.16.2
-
pytorch==0.4.1
-
tensorflow==1.7
-
gensim==3.7.1
-
tensorboardX==1.6
- Make sure the raw data, meta data are in the same direction.
- Preprocessing data. Filter the review to each user having at least 10 transactions. Remove the words whose number is less than
count
. Split the data into three sets and extract queries.python extract.py --review_file --meta_file --count=5
- We leverage the PV-DM model to convert queries and product representations to the same latent space.
python doc2vec.py --window_size=3
- Start training the model.
python main.py --lr=0.001 --num_steps=4 --alpha=0.9