College - Author 1
College of Engineering
Department - Author 1
Computer Engineering Department
Degree Name - Author 1
BS in Computer Engineering
College - Author 2
College of Engineering
Department - Author 2
Computer Science Department
Degree - Author 2
BS in Computer Science
Date
3-2021
Primary Advisor
Christopher Siu, College of Engineering, Computer Science and Software Engineering Department
Abstract/Summary
Real estate agents are often tasked with finding their clients’ ideal properties. This can be difficult because multiple clients may have varying preferences, such as number of bedrooms, square footage, or price. Furthermore, different clients may weight their individual preferences differently. Existing applications do not consider multiple clients’ satisfaction, nor do they allow clients to weigh their preferences, potentially leading to less-than-ideal matchings between clients and properties.
In this project, we design and implement an iOS application whereby real estate agents can match multiple clients with individually weighted preferences to properties scraped from web listings. We model this client-property matching problem as a weighted graph, and apply the Kuhn–Munkres algorithm to find matchings that lead to the greatest overall client satisfaction.
URL: https://digitalcommons.calpoly.edu/cscsp/153