The AutoPath pipeline for similarity modeling on heterogeneous networks with automatic path discovery

Carl Yang, Mengxiong Liu, Frank He, Xikun Zhang, Jian Peng, Jiawei Han, "Similarity Modeling on Heterogeneous Networks via Automatic Path Discovery", ECML/PKDD 2018.

AutoPath is implemented with TensorFlow and Python2. Please make sure you have the newest version of both of them. If not sure, simply run

pip2 install --upgrade pip
pip2 install --upgrade tensorflow

Use the following commands to run train the AutoPath model on our default IMDb dataset.

cd model
python2 train.py

You may also change the parameters as you like in config.py. With our default parameter settings, training the model roughly takes a few minutes on CPU. Note that, you need to remove the \tmp folder if you change the neural network structures before training a new model.

Use the following command to play with the trained AutoPath model.

python2 demo.py

This demo basically allows you to look for similar movies regarding genres. Note that finding movies with exactly the same set of genres is very challenging, because genres can be multiple and ambiguous. Nonetheless, our results show that most movies returned by our model at least share a few genres with the queried movie. To play with the demo, input one or more movie ids (separated by space) at each time.

0

or

0 1 2

Top 10 related movies for <the_van>, ['Comedy', 'Drama']
<michael_collins>, ['Drama', 'Biography', 'Thriller', 'War']
<the_butcher_boy>, ['Comedy', 'Drama']
<his_girl_friday>, ['Comedy', 'Romance', 'Drama']
<the_madness_of_king_george>, ['Comedy', 'Drama', 'Biography', 'History']
<the_cook_the_thief_his_wife_&_her_lover>, ['Crime', 'Comedy', 'Horror', 'Romance', 'Drama']
<tin_men>, ['Comedy', 'Drama']
<the_beverly_hillbillies>, ['Comedy', 'Family']
<an_american_in_paris>, ['Romance', 'Musical']
<sweet_nothing>, ['Drama']

If you have any questions about the code or data, please feel free to contact me.