NlpTools

Spam detection as a service Mar 7th, 2013

For the first mini nlp project we will create a spam detection service for use with email systems and probably any system. Our purpose is to create an HTTP endpoint (REST service) that will be managing models (create / train / classify / delete). The classifier will be a binary classifier with the class names being SPAM and HAM for spam and not spam accordingly.

The purpose of the service we will create is not to make well known anti-spam services obsolete, it is to create a good starting ground for using NlpTools for Bayesian classification and for creating a custom classifier that given a specific context (and extra work by you) could even outperform well known solutions.

Classification model to use

At the time of writing, NlpTools only supports two models Naive Bayes and Maximum Entropy (conditional exponential model). Although Maximum Entropy models are known to perform better at most NLP tasks I will be using NaiveBayes for the following reasons:

1. NB is a lot less computationally intensive to train than MaxEnt
2. Because of reason 1 we can use pure php and still create a usable for real world scenarios service
3. We can incrementally train a NB model without keeping all the previous documents (we will be keeping a training context)

Service overview

We want to be able to perform the following functions

1. Create a model
2. Train a model on a set of emails (report emails as spam)
3. Classify a set of emails
4. Delete a model

This means we will at least have 4 endpoints at our RESTful service. Let's also use JSON as the only transport format so as to not complicate things.

Tools

We will now setup our environment. Besides the obvious, NlpTools, we will also be using Silex to help us out with building our service. We will be installing both using composer. Create a directory to hold the project (ex.: spam-service), then create a composer.json .

{
    "require": {
        "silex/silex": "1.0.*@dev",
        "nlp-tools/nlp-tools": "1.0.*@dev"
    },
    "autoload": {
        "psr-0": {"": "web/"}
    }
}

It is also obvious from the above composer.json file that we will be coding in the web directory and that our code namimg conventions will comply to the psr-0 standard. Now run composer to install silex and NlpTools and their dependencies. If you don't have composer run the following.

$ curl -s http://getcomposer.org/installer | php
$ composer.phar install

Finally, for the first part we need to setup a webserver that will serve our spam service. Silex documentation has plenty of information to setup silex to play with any webserver. I will add the config file I am using for nginx.

server {
    listen localhost:80;
    server_name 127.0.0.1;

    location / {
        # example: unix:/var/run/php-fpm/www.sock
        fastcgi_pass unix:/path/to/spam-service/spam-service.sock;
        include fastcgi_params;
        # replace /path/to/spam-service with whatever directory you
        # created to put the project in
        fastcgi_param SCRIPT_FILENAME /path/to/spam-service/web/index.php;
    }
}