Unsupervised Learning

Clustering of documents

Topic modeling is a method for unsupervised classification of such documents, similar to clustering on numeric data, which finds natural groups of items even when we’re not sure what we’re looking for.

• It treats each document as a mixture of topics, and each topic as a mixture of words.

This allows documents to “overlap” each other in terms of content, rather than being separated into discrete groups, in a way that mirrors typical use of natural language.

• Every document is a mixture of topics.
• Every topic is a mixture of words.

The example in the book runs topic analysis on the Associated Press articles from around 1988.

The two topics found are Financial News and Politics.

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