Taxonomy of keyword extraction in Facebook using Decision Tree algorithm in NLP

Abstract

The main idea of our project is to extract keywords from the collection of dataset from Facebook account data like comment, post by the people. Then, By extracting the keywords from the specific account, we can provide the advertisement with help of the business organizations, to improve the business growth of each organization. Text can be an extremely valuable source of information, but extracting insights from the data can be hard and time-consuming due to its unstructured nature. Businesses are performing to text classification for structuring text in a fast and cost-efficient way to enhance decision-making and automate processes in the model. Instead of relying on manually crafted rules, text classification in machine learning learns to make classifications based on past observations. By using pre-labelled examples as training data, a machine learning algorithm can learn the different subset between pieces of text and that a particular output is expected for a particular input.