Bag of words Model using NLTK lib
Bag of words is a Natural Language Processing technique of text modelling. Through this blog, we will learn more about why Bag of Words is used, we will understand the concept with the help of an example, learn more about it’s implementation in Python, and more.Using Natural Language Processing, we make use of the text data available across the internet to generate insights for the business. In order to understand this huge amount of data and make insights from them, we need to make them usable. Natural language processing helps us to do so.
Bag of words is a Natural Language Processing technique of text modelling. In technical terms, we can say that it is a method of feature extraction with text data. This approach is a simple and flexible way of extracting features from documents.
A bag of words is a representation of text that describes the occurrence of words within a document. We just keep track of word counts and disregard the grammatical details and the word order. It is called a “bag” of words because any information about the order or structure of words in the document is discarded. The model is only concerned with whether known words occur in the document, not where in the document.