Deep Learning Recommendation System for Property Management Software

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About the Project

We created a recommender system that predicts users interests and recommends properties to users based on previous user interactions and property features. Recommender systems are among the most powerful machine learning systems that are used to help users identify items they may be interested in and also helps companies increase interaction and sales. Our sponsor is AppFolio, a tech company based in Santa Barbara that provides innovative software, services, and data analytics to the real estate industry. Building this model will allow AppFolio to analyze the results of our recommender system to assess how interaction data can be used to better their products. We explored multiple models including the Bilateral Variational Autoencoder (BiVae), TriVae, Visual Bayesian Personalized Ranking (VBPR), and Deep Cross Network (DCN) in an effort to achieve the highest prediction accuracy using 16 property features from our given dataset and images. Ultimately, we want to integrate our model into the Santa Barbara property website, which was built by the AppFolio Sponsored CS Capstone team.


  Student Team

  • Alyssa Keehan
  • Joshua Harasaki
  • Romina Fareghbal
  • Philip Carey
  • Jordan Tran


  • Shyr-Shea Chang, Sponsor
  • Soeren Thust, Sponsor
  • Erika McPhillips, TA


About AppFolio

AppFolio offers industry-specific business software solutions, services, and data insights to the real estate markets. Ranked the #1 Fastest Growing Company in 2020 by Fortune Magazine, AppFolio is headquartered in Santa Barbara, but has offices in Los Angeles, San Diego, Dallas, and Boston. The company's services are used throughout the U.S.A. Their primary product is the AppFolio Property Manager, which provides solutions to property managers and rental agencies. This cloud-based application offers services such as the collection of rent, document processing, and the coordination of third-party vendors and services (such as hiring plumbers or electricians).