Building an Intelligent Online Shopping Assistant Using Data Mining Techniques for E-Commerce platforms

​In this project, we develop an online shopping assistance using data mining technique for e-commerce platform. Artificial intelligent (AI) has the powerful ability to acquire and analyze large volume of data and provide decision for action-commerce is now adopting this technology to identify patterns on browsing, purchase history credit check account information etc. Big data start with large volume, heterogeneous autonomous sources with distributed and decentralized control; and seeks to explore complex and evolving relationships among data so they can personalize and help in meeting better requirement of users. The objective of this project is to develop an intelligent system that can assist e-commerce user using data mining technique called clustering; this method cluster the string and matches words with neighbors. A counter is use to count the number of string matched in compared files. The methodology adopted for this system is the Structured System Analysis Design Methodology (SSADM); the agile software development lifecycle will be used in the software development. The primary mode of data collection was carried out using JUMIA and KONGA e-commerce portal, while the secondary mode was achieved using e-books, journals and libraries. The expected result of the project show an online shopping assistant will be integrated into e-commerce platform and will showcase item to the user base on criteria mined from their data records such as their past sales and personal preferences. The system contains both users-ends; this dashboard showcase the item to customers as their past sales and personal preference and the admin dashboard is where product, price and grades are located. The instrument used on the system are bootstrap which comprises of HTML and CSS; MySQLi for the database.