Using APIs to classify text
We will use OpenNLP, Stanford API, and LingPipe to demonstrate the various classification approaches. We will spend more time with LingPipe as it offers several different classification approaches.
Using OpenNLP
The DocumentCategorizer interface specifies methods that can be used to support the classification process. The interface is implemented by the DocumentCategorizerME class. This class will classify text into predefined categories using a maximum-entropy framework. In this section, we will do the following:
- Demonstrate how to train the model
- Illustrate how the model can be used
Training an OpenNLP classification model
First, we have to train our model because OpenNLP does not have prebuilt models. This process consists of creating a file of training data and then using the DocumentCategorizerME model to perform the actual training. The model that is created
is typically saved in a file for later use.
The training file format consists of a series of lines where...
