Topic Modeling is an efficient way to organize, understand and summarize large volumes of text. With huge amount of text data getting generated everyday, it becomes challenging to access the most relevant information. Topic modeling helps us in efficient text browsing by:
- Discovering hidden topical patterns present across the corpus
- Annotating each document according to these topics
- And finally, these annotations can be used to organize, search and summarize texts
Topic Modeling is a method for finding a group of words from a collection of documents that best represents the information in the collection. It can also be thought of as a form of text mining - a way to obtain recurring patterns of words in text. While there are many different algorithms for topic modeling, the most common is Latent Dirichlet Allocation, or LDA.