opentc 0.5.0
A text classification engine using machine learning and designed as client-server architecture
License: MIT
Keywords: machine learning cnn svm bayesian

Open Text Classification (OpenTC)
=================================

OpenTC is a text classification engine using machine learning. It is
designed as client-server architecture and uses python libraries
scikit-learn and tensorflow for it's machine learning algorithms.
Currently following algorithms are supported:

-  Naive Bayes
-  Support Vector Machine
-  Convolutional Neural Network

In the future it will also support FastText from Facebookresearch.

The engine is running as a server listening on command and text to be
classified. By default it listens on localhost port 3333, but it can be
changed in the yaml configuration file.

OpenTC can be used for example for text classification (a demo website
for this purpose is available online `OpenTC
demo <http://opentc.oldjava.org/demo/>`__), or for other purposes such
as Data Leak Prevention (DLP). An example of implementation for the DLP
has been created as ICAP Server:
`opentc-icap <https://github.com/cahya-wirawan/opentc-icap>`__

Requirements
------------

-  Python 3.x
-  numpy
-  pyparsing
-  PyYAML
-  scikit-learn
-  scipy
-  tensorflow 1.x

How to use
----------

Installation
~~~~~~~~~~~~

Install the module using pip:

::

    $ pip install opentc

or clone the repository

::

    $ git clone https://github.com/cahya-wirawan/opentc.git
    $ cd opentc
    $ python setup.py install

opentc
~~~~~~

synopsis
^^^^^^^^

opentc

Description
^^^^^^^^^^^

The command line to train the application based on the datasets define
in the configuration file. The result of the training (pre-trained data)
can be used for the opentcd server.

Usage
^^^^^

::

    $ python opentc -h
    usage: opentc [-h] [-c CLASSIFIER] [-C CONFIGURATION_FILE] [-d DATASET]
                  [-l LOG_CONFIGURATION_FILE]

    optional arguments:
      -h, --help            show this help message and exit
      -c CLASSIFIER, --classifier CLASSIFIER
                            set classifier to use for the training (support
                            currently bayesian, svm or cnn)
      -C CONFIGURATION_FILE, --configuration_file CONFIGURATION_FILE
                            set the configuration file
      -d DATASET, --dataset DATASET
                            set dataset to use for the training
      -l LOG_CONFIGURATION_FILE, --log_configuration_file LOG_CONFIGURATION_FILE
                            set the log configuration file

opentcd
~~~~~~~

synopsis
^^^^^^^^

opentcd

Description
^^^^^^^^^^^

The daemon listens for incoming connections on TCP port (default is
3333) and classify files or text string on demand. It reads a
configuration file in the following order: ./opentc.yml,
~/.opentc/opentc.yml or /etc/opentc/opentc.yml.

Usage
^^^^^

Opentcd uses the configuration file opentc.yml to define allmost all
possible configuration. Only few setup can be overridden in command line
options.

List of arguments:

::

    $ python opentcd -h
    usage: opentcd [-h] [-a ADDRESS] [-C CONFIGURATION_FILE]
                   [-l LOG_CONFIGURATION_FILE] [-p PORT] [-t TIMEOUT]

    optional arguments:
      -h, --help            show this help message and exit
      -a ADDRESS, --address ADDRESS
                            define the address for the server
      -C CONFIGURATION_FILE, --configuration_file CONFIGURATION_FILE
                            set the configuration file
      -l LOG_CONFIGURATION_FILE, --log_configuration_file LOG_CONFIGURATION_FILE
                            set the log configuration file
      -p PORT, --port PORT  define the port number which the server uses to listen
      -t TIMEOUT, --timeout TIMEOUT
                            define the time out

Run it as background application:

::

    $ python opentcd&
    2017-05-02 13:33:22,276 - opentc.core.classifier.cnn_text - DEBUG - Load the checkpoint: 
    data/input/cnn_twenty_newsgroup_20170301_090000-all/checkpoints/model-2210
    INFO:tensorflow:Restoring parameters from data/input/cnn_twenty_newsgroup_20170301_090000-all/checkpoints/model-2210
    2017-05-02 13:33:23,899 - tensorflow - INFO - Restoring parameters 
    from data/input/cnn_twenty_newsgroup_20170301_090000-all/checkpoints/model-2210
    2017-05-02 13:33:27,375 - __main__ - INFO - Server start
    2017-05-02 13:33:28,019 - opentc.core.server - INFO - Server loop running in thread: Thread-1

datasets and pre-trained data
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

The configuration file defines the path to the datasets and pre-trained
data. A pre-trained data for testing purpose can be downloaded from
`data <https://NoFile.io/f/6ZkDvJH0nT4>`__, it is around 1.4GB. Just
uncompress it and change the path to the pre-trained data in opentc.yml
file accordingly.

Commands
^^^^^^^^

The command uses a newline character as the delimiter. If opentcd
doesn't recognize the command, or the command doesn't follow the
requirements specified below, it will reply with an error message, but
still wait for the next commands (this behaviour can be changed in the
future).

PING
''''

Check the server's state. It should reply with "PONG".

VERSION
'''''''

Print the program version

RELOAD
''''''

Reload the engine

LIST\_CLASSIFIER
''''''''''''''''

List the supported classifiers (at the moment there are three
classifiers supported: Bayesian, Support Vector Machine and
Convolutional Neural Network). It shows also the status of classifier,
either True (enabled) or False (disabled).

SET\_CLASSIFIER
'''''''''''''''

Enabled or disabled the specific classifier

PREDICT\_STREAM
'''''''''''''''

Classify text streams. It uses a new line character as delimiter for
every sentences.

PREDICT\_FILE
'''''''''''''

Classify file. It uses a new line character as delimiter for every
sentences

CLOSE
'''''

Close the connection

Todo
----

-  Multilabel classification
-  Include FastText from Facebookresearch
-  Will use pyzmq and google's protobuf to improve the protocol and
   network communication