Master project about recommender systems.

How to use

#. Reading recommender's specifications from config/recommender.json, we run our recommender is made through the runnables.py script, using the command: ::

 make run

#. Reading experiment's specifications from config/runs.json, we run a full experiment is made through the runnables.py script, using the command: ::

 make experiment

#. The running options are available using the command ::

 python3 runnables.py -h

Testing

#. Running the runtests.py script, will run the tests in tests.tests: ::

  make test

#. Running the runtests.py script, with arguments that contain the modules of the unittests, will run the tests in all the provided modules. ::

  python runtests.py test1 test2 test3 # ...

Database

We are mainly using citeulike datasets, we assume that the data files are in the directory data/, and the database configuration from config/config.json

To build the database, we run the command: ::

  make rebuild-database

We execute this statement in MySQL console before importing the data: ::

  set autocommit = 0;

Documentation

To generate the documentation we can use the command: ::

  make docs

Linting

We are following flake8 code conventions, we can verify it using the command: ::

  make lint-flake8

Authors

Authored by:

Mostafa M. Mohamed mostafa.amin93@gmail.com
Omar Nada ndomar.14@gmail.com
Ibrahim Alshibani ibrahim.alshibani@gmail.com

Requirements

pep8
python-coverage
mysql-client
mysql-server
mysql-python
json
sklearn
numpy
sphinx
scipy
overrides
tensorflow
keras
pandas
lda2vec
spaCy
chainer
python-dev

Issues and TODOs

https://github.com/mostafa-mahmoud/HyPRec/issues

License

HyPRec is licensed under the Apache License 2.0

HyPRec

Install / Use

README