Applying Recommender Approaches to the Real Estate e-Commerce Market

  • Like in many other branches of modern economies, the internet changed the behavior of suppliers and customers in real estate markets. Recommender systems became more and more important in providing customers with a fast and easy way to find suitable real estate items. In this paper, we show different possibilities for embedding the recommendation engine into the user journey of a real estate portal. Moreover, we present how additional information regarding real estate items can be incorporated into the recommendation process. Finally, we compare the recommendation quality of the state-of-the-art approaches deep learning and factorization machines with collaborative filtering (the currently used recommender algorithm) based on a data set extracted from the productive system of the Immowelt Group.

Export metadata

Additional Services

Search Google Scholar
Metadaten
Author:Julian Knoll, Rainer GroßORCiD, Axel Schwanke, Bernhard Rinn, Martin Schreyer
DOI:https://doi.org/10.1007/978-3-319-93408-2_9
ISBN:9783319934075
ISSN:1865-0929
Parent Title (English):Communications in Computer and Information Science
Publisher:Springer International Publishing
Place of publication:Cham
Document Type:Part of a Book
Language:English
Reviewed:Begutachtet/Reviewed
Release Date:2025/01/27
Pagenumber:16
First Page:111
Last Page:126
institutes:Fakultät Informatik
Research Themes:Digitalisierung & Künstliche Intelligenz
Verstanden ✔
Diese Webseite verwendet technisch erforderliche Session-Cookies. Durch die weitere Nutzung der Webseite stimmen Sie diesem zu. Unsere Datenschutzerklärung finden Sie hier.