Rental Property Recommendation System Based on Fuzzy Decision Tree

ABSTRACT Various recommender systems are currently popular for recommending content to users based on different parameters. Due to the scarcity of historical data on users' house rental behavior, the system suffers from the cold‐start problem. This paper introduces a house rental recommendation system utilizing a fuzzy decision tree, comprising three sub‐modules: User Interface, User and Housing Database, and Housing Recommendation System. The system aims to suggest suitable properties to tenants by processing user and house information to generate a list of recommended houses through a house matching module. The proposed system attains 99.6% Recall, 88.6% Precision, and 93.7% F1‐score, demonstrating excellent performance on standard evaluation metrics. It outperforms comparable methods, making a significant contribution by establishing a comprehensive recommendation system using a fuzzy decision tree for house rentals. The system's efficacy is validated with real users and compared against similar methods and the recommendation module of another online house rental platform.