In this chapter, we will learn about the basics of topic modeling using a document that contains some text. The idea here is to get the topic from the text using certain available methods. This process falls under the category of text mining, and plays an important role in searching as well as clustering and organizing text. Today, it is used by many sites for recommendation purposes, such as when news sites recommend articles based on the topic of the article that is currently being read by the reader. This chapter covers the basics of topic modeling, including the basic concept of Latent Dirichlet Allocation (LDA). It will also show you how to use the MALLET package for topic modeling.

We will cover the following topics in this chapter:

• What is topic modeling?
• The basics of LDA
• Topic modeling with MALLET