Now that you have a sense of how topics are defined, let’s define the task of topic modelling more formally. first, let’s define the input and the output (s) of a topic model.
The input to a topic model is the corpus of documents, for e.g. a set of customer reviews, tweets, research papers, books etc.
There are two outputs of a topic model-1. the distribution of topics in a document and 2. the distribution of words in a topic. In the following figure, the first matrix is the probability distribution of words in a topic, while the second matrix is the distribution of topics in a document.
In the subsequent lectures, you’ll learn how to get the output from the given set of documents.