The location of a residential property in a city directly affects its market price. Each location represents different values in variables such as accessibility, neighbourhood, traffic, socio-economic level and proximity to green areas, among others. In addition, that location has an influence...

In this paper, we introduce a novel tool for housing market analysis developed on the basis of online listings data from the largest real estate listing site in Denmark. The tool uses a combination of machine learning techniques to provide a datadriven segmentation of the housing market into...

Having forecast of real estate sales done correctly is very important for balancing supply and demand in the housing market. However, it is very difficult for housing companies or real estate professionals to determine how many houses they will sell next year. Although this does not mean that a...

This is the first study to use the self-organisation (Kohonen) map technique, an artificial neural network based on a non-supervised learning algorithm, to categorise Vietnamese banks into super-class groups. Drawing on unbalanced yearly data from 2008 to 2017, this study identifies two...