Natural Language Understanding with Python

12

Applying Unsupervised Learning Approaches

In earlier chapters, such as Chapter 5, we discussed the fact that supervised learning requires annotated data, where a human annotator makes a decision about how a natural language processing (NLP) system should analyze it – that is, a human has annotated it. For example, with the movie review data, a human has looked at each review and decided whether it is positive or negative. We also pointed out that this annotation process can be expensive and time-consuming.

In this chapter, we will look at techniques that don’t require annotated data, thereby saving this time-consuming step in data preparation. Although unsupervised learning will not be suitable for every NLP problem, it is very useful to ...