Using Artificial Intelligence in Real Estate: Can we build more effective recommendation systems?
Problem Statement:
Geo-analytics is about the use of location-based information in analyses for contextual awareness and situational understanding. This information usually comes from high-spatial-resolution satellite imagery. By incorporating geo-location and other spatial details, businesses can gain a broader understanding of big data scattered in physical space and time, uncovering new insights and new efficiencies. The use of geo-analytics enables comparisons among different locations and may be used to identify trends and patterns, both locally and regionally. Geo-analytics is usually combined with artificial intelligence and computer vision, to perform high-resolution land cover mapping and identify cues that describe the quality and condition of buildings, to understand their status and market value.
Task:
The general aim of the project is to employ advanced geo-analytics based on 27 environmental services, using the island of Cyprus as a testbed, to propose a recommender system, using state-of-art research in recommendation engines, which provides meaningful recommendations to potential buyers of properties. The list of services is provided here: https://superworld.cyens.org.cy/product1.html
while you can get a flavor of how each service works via the GAEA online too: https://superworld.cyens.org.cy/product3.html
Work:
20% Theory, 40% Modelling, Coding and Testing, 20% Evaluation and Validation, 20% Writing
Contact:
Andreas Kamilaris: a.kamilaris@utwente.nl