Prediction car prices using quantify qualitative data and knowledge-based system

Car pricing using machine learning has a strong relationship with the process of knowledge acquisition for expert systems. Recently, the primary technique for knowledge acquisition has been the time-consuming process of recommendation, posting for car buying or selling on internet market websites. After discovering the data, we can divide that into two types: structured and unstructured that require knowledge-based analysis. This paper will involve the techniques for extraction of meaning, data inference, and rules for qualitative data. The main purpose of the current research is to explore different data types of car data and the objective is to create an automated technique to predict car prices.