Recommendation Engine Development for Real State Marketplace App

Abstract

The goal of this project is to create a recommendation engine for Casafy, a Proptech startup that wants to develop a Real Estate Marketplace App in Brazil. For this, first a Rule-based recommendation system will be developed as a placeholder in order to collect user interaction data. Afterwards, two Machine learning Recommendation Engines will be developed making use of user's, real estate property's and aforementioned interaction data. These two models will be a matrix factorization based collaborative filtering system and a model-based system. An ablation study will be conducted to examine the contribution of each individual component in the data. Finally, their performance will be compared using several metrics, such as rmse, micro f1, macro f1 and hamming loss to evaluate and decide which architecture will be used for the final product.