Roomsemble: Progressive web application for intuitive property search

TL;DR

Roomsemble is a web app that personalizes property searches by matching user-provided photos of personal taste with similar real estate listings, integrating filters for budget and location.

Contribution

It introduces a novel system that captures personal aesthetic preferences through photos to improve property recommendation accuracy.

Findings

Tested with 25 users showing promising personalization results.

Demonstrated effective integration of aesthetic preferences into property search.

Provided insights into user preferences based on photo-based taste modeling.

Abstract

A successful real estate search process involves locating a property that meets a user's search criteria subject to an allocated budget and time constraints. Many studies have investigated modeling housing prices over time. However, little is known about how a user's tastes influence their real estate search and purchase decisions. It is unknown what house a user would choose taking into account an individual's personal tastes, behaviors, and constraints, and, therefore, creating an algorithm that finds the perfect match. In this paper, we investigate the first step in understanding a user's tastes by building a system to capture personal preferences. We concentrated our research on real estate photos, being inspired by house aesthetics, which often motivates prospective buyers into considering a property as a candidate for purchase. We designed a system that takes a user-provided photo representing that person's personal taste and recommends properties similar to the photo available on the market. The user can additionally filter the recommendations by budget and location when conducting a property search. The paper describes the application's overall layout including frontend design and backend processes for locating a desired property. The proposed model, which serves as the application's core, was tested with 25 users, and the study's findings, as well as some key conclusions, are detailed in this paper.