Automatic Product Recommendation and Price Comparison System Based on User's Preferences

The method of shopping gradually changed from physical stores to virtual stores since the famous and various web commerce platforms created. Consumers can choose their desired products though more stores and get lower price than physical stores via virtual ones. However it is a time-consuming task to surfing lots of different e-commerce platforms and perform the analysis to get the best one. It is really an additional burden. The purpose of this project is to design and implement an automatic recommendation system based on commodity information commodity preferences of different users. In order to complete such a system, this project will be divided into two years. The first year of this research project will focus on how to collect, analyze and build affordable commodity prices and the architecture and schema of database with suitable file system. The second year of this project will focus on how to find out user preferences products and user preferences in the first year to establish a connection between both sides. It also recommends relative products to the user according to users’ behaviors. This project can collect useful products information for further research subjects and also can train students to have the skills of big-data and web technology.

Project ID:PB10408-5758
External Project ID:MOST104-2221-E182-069