Abstract
Property valuation is a complex and time-consuming process which is carried out by qualified real estate appraisers. Number of properties and number of purchase-sale transactions grows year by year. Mass real estate appraisal appears as another big problem. These issues are connected with deficiency of human and time resources. Therefore, numerous studies are carried out on computer systems which can support the real estate appraisers. Automated property valuation systems are also developed. A method utilizing clustering algorithms to automate property valuation according to sales comparison approach was proposed in this paper. A crisp and fuzzy clustering algorithms were employed to divide the properties located in a given city into a number of clusters. These clusters established the basis for property valuation process. The effectiveness of the proposed method was examined and compared with the real estate appraisal based on the spatial partition of an area of the city into cadastral regions and expert zones.
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Malinowski, A., Piwowarczyk, M., Telec, Z., Trawiński, B., Kempa, O., Lasota, T. (2018). An Approach to Property Valuation Based on Market Segmentation with Crisp and Fuzzy Clustering. In: Nguyen, N., Pimenidis, E., Khan, Z., Trawiński, B. (eds) Computational Collective Intelligence. ICCCI 2018. Lecture Notes in Computer Science(), vol 11055. Springer, Cham. https://doi.org/10.1007/978-3-319-98443-8_49
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