In very simple terms, topic modeling is a technique by which the computer programs try and extract a topic from the text. The text is usually unstructured data, such as a blog, email, article, a chapter from a book, or something similar. It is a text-mining approach, but should not be confused with rule-based text mining. In a machine learning scenario, topic modeling falls under the category of unsupervised learning, where the machine or computer program tries to find the topic by observing a bunch of words in the last collection of text. A good model should result in the words "program", "programmer", "IT", "computer", "software", and "hardware" when given the topic of "IT industry". It helps in making sense of large text, and plays a vital role in the operation of search engines.
Topic modeling can be used with methods to organize, categorize, understand, and summarize large collections of textual information. It enables us to discover hidden patterns in collections...