Recommendation Systems Applied in Turkish Real Estate Market

Journal of Computations & Modelling, Vol. 10, No. 1, 2020, 1-10

10 Pages Posted: 17 Apr 2020

See all articles by Mehmet Erkek

Mehmet Erkek

affiliation not provided to SSRN

Kamil Çayırlı

affiliation not provided to SSRN

Hakan Taş

affiliation not provided to SSRN

Ali Hepsen

Istanbul University - Faculty of Business Administration, Department of Finance

Tevfik Aytekin

affiliation not provided to SSRN

Date Written: March 24, 2020

Abstract

Today consumers are confronted with a very large number of products and services to choose from. This makes it difficult for users to find relevant products among a huge number of alternatives. A recommendation system is an extensive class of web applications that involves predicting the user responses to the options and helps users to find products of interest by analyzing their past transactions such as product views and purchases. There is also a similar problem in the real estate industry where thousands of properties are available for rentals or sales. In this work we firstly presented the details of a real estate recommender system developed for Zingat.com and then, we explained how we implemented a fully functional recommendation system for property listings in Turkey. Since the number of listings is huge and new listings come and go frequently, it is a challenge to build a successful recommender system. We tackled this challenge by building a system which uses collaborative filtering and content-based filtering, separately. We also designed a scalable system architecture which can function under heavy load. In the future we plan to further improve this system by using diversification techniques and new solutions.

Keywords: Artificial Intelligence, Machine Learning, Real Estate, Recommendation Engine, Zingat.com

JEL Classification: C00, C20, C60

Suggested Citation

Erkek, Mehmet and Çayırlı, Kamil and Taş, Hakan and Hepsen, Ali and Aytekin, Tevfik, Recommendation Systems Applied in Turkish Real Estate Market (March 24, 2020). Journal of Computations & Modelling, Vol. 10, No. 1, 2020, 1-10, Available at SSRN: https://ssrn.com/abstract=3560126

Mehmet Erkek

affiliation not provided to SSRN

Kamil Çayırlı

affiliation not provided to SSRN

Hakan Taş

affiliation not provided to SSRN

Ali Hepsen (Contact Author)

Istanbul University - Faculty of Business Administration, Department of Finance ( email )

Istanbul
Turkey

Tevfik Aytekin

affiliation not provided to SSRN

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