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A good prediction of the target customer group is very important for developers and sellers of flats or apartments. In this paper, a system, which predicts a group of people who would be interested in the available flat based on its design and localization, is proposed. The described model extends the typical linear process of designing/building/selling a flat into a cooperative one, allowing potential buyers to provide their preferences regarding a place to live. The model includes a specially built website for data collection, where floor layouts augmented with the additional information are assessed by four different groups of people, as well as four multi-class classifiers trained on the dataset obtained from the collaborative assessments of flats.

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Collaborative Assessment of Apartments for Predicting a Potential Customer Group by Machine Learning Algorithms

  • 会议论文

  • 发表日期：

    2026年

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  • Barbara Strug,
  • Grażyna Ślusarczyk

摘要

A good prediction of the target customer group is very important for developers and sellers of flats or apartments. In this paper, a system, which predicts a group of people who would be interested in the available flat based on its design and localization, is proposed. The described model extends the typical linear process of designing/building/selling a flat into a cooperative one, allowing potential buyers to provide their preferences regarding a place to live. The model includes a specially built website for data collection, where floor layouts augmented with the additional information are assessed by four different groups of people, as well as four multi-class classifiers trained on the dataset obtained from the collaborative assessments of flats.