A Comparitive Analysis of Customer Behaviour Using Sophisticated Machine Learning - E. Nagarjuna, M. Suresh, L. Eswaramma, P. Kiran, M. Akshitha Laasya (Mathematical Statistician and Engineering Applications, 2023)
Data is growing in leaps and bounds day by day with the rapid growth in cloud and internet technologies. Social media has become an integrated part of life as it is used to share content, opinions, reviews, suggestions etc. Anybody can voice out their opinions through social media. This data can be reused or analyzed to understand the customer and cater to his needs. In particular, e-Commerce platform enable the users to write product reviews to help other buyers purchase better products and be benefited from their opinions. The e-Commerce platform can also mine the data for sentiment analysis to understand the customer opinion and build recommendation systems to understand the customer needs and suggest products. Recommendation systems give a personalized shopping experience to users and there by increases sales and profits. In this project we use n-gram analysis to understand the data in the dataset and then apply multiple machine learning algorithms to the selected dataset to identify the appropriate classification algorithm that gives the best accuracy. We also try to build a recommender system that uses collaborative filtering to recommend appropriate products as per the customer needs.