Personalized grocery' basket recommendation using content-based filtering algorithm / Fatin Nadhirah Azland

With the emergence of e-commerce, recommendation system has become a demand to recommend the right items to the right users. Recommendation system is a part of data mining, which is a process of obtaining useful information from a large amount of data. There are two problems that initiates the development of this project. One is the users having difficulty to identify which website that gives the best recommendation for the item they want, and the other problem is time consuming for customers to find the right items. For this project, literature study is done to understand the best approach to solve problems, then the system is developed using Python language with interfaces, and lastly evaluation is done to test the accuracy. The output that are shown to users are the item being recommended with its price and the website being collected. This project achieved all the objectives but has several limitations such as not optimal evaluation method, lack of user interface and the strict user input.