PurposeIn the real estate business, identifying the ideal property for a user poses a difficult task due to the many factors involved in the decision-making process. Moreover, users often struggle to find platforms that facilitate effective communication of their preferences. To tackle this issue, a web-based data-driven recommendation system has been devised for the real estate business.Design/methodology/approachThe process of identifying the most suitable rental property for a user hinges greatly on how the user prioritizes each criterion and the analysis of unstructured data. In this research, a novel recommendation system for house rentals is developed by utilizing the Weighted Hierarchical Fuzzy Axiomatic Design (WFAD) approach. Techniques for extracting pertinent information from unstructured house descriptions are employed. The user’s preferences are captured through an interactive web application equipped with a map feature to highlight key locations.FindingsData on various available rental properties are gathered using web scraping techniques. The efficacy of the proposed rental house recommendation system is demonstrated through multiple case studies. It is observed that the developed system provides more informed and reliable decisions.Originality/valueFirst time in the related literature, we applied the weighted fuzzy axiomatic design procedure (WFAD) to the product recommendation problem and developed a comprehensive web-based system for recommending rental houses based on it in the real estate business.
