Mehran-k / RelNN

RelNN is a novel first-order deep neural model for relational learning.

Geek Repo:Geek Repo

Github PK Tool:Github PK Tool

Summary

The source code and the datasets used for the experiments in my "Relational Aggregation using First-Order Deep Neural Models" paper to appear at AAAI-18.

How to access the datasets:

The MovieLens 1M dataset is in datasets/ml-1m folder. It can be also downloaded from the this link. The Yelp! and KDD datasets are in datasets/yelp_mc.db and datasets/KDD15_123.db respectively. Please read the terms of use for these datasets before using them.

How to run the code:

Make sure you have java JDK installed on your machine. Compile the code using the following command (note that the command starts after $):

$ javac *.java

Then for each experiment, run the corresponding class:

$ java <ClassName>

For instance to run the experiemnts on the Yelp! dataset, run:

$ java YelpMC

The other classes are called MovieLensGender, MovieLensAge, and KDD.

Contact

Seyed Mehran Kazemi

Computer Science Department

The University of British Columbia

201-2366 Main Mall, Vancouver, BC, Canada (V6T 1Z4)

http://www.cs.ubc.ca/~smkazemi/

smkazemi@cs.ubc.ca

License

Licensed under the GNU General Public License Version 3.0. https://www.gnu.org/licenses/gpl-3.0.en.html

Copyright (C) 2017 Seyed Mehran Kazemi

About

RelNN is a novel first-order deep neural model for relational learning.

License:Other


Languages

Language:Java 100.0%