For this project the company wants to show personalized search results for holiday destinations on their website. Currently, the company 's system makes recommendations of search results based on deterministic queries on SQL. These search results offer matching results based on keywords. However, these results may not reflect the user 's personal interests or preferences, and may miss out on similar or alternative destinations or hotels that the user may find more appealing.
VDU records all users ' interaction with their website. This data contains history of user’s purchases and liked destinations. They want to use this data to potentially recommend other destinations to their customers which could increase conversion(sales) rates.
The aim of this project is to design and implement a machine learning-based recommendation system that can generate personalized search results for users based on their past booking history, current website interaction, and other factors. The project will follow the software development lifecycle (SDLC) phases of planning, analysis, design, implementation, testing, and deployment. The project will also involve data processing, and analysis to build and evaluate machine learning models which leads to recommendations of high accuracy.