Real Estate Ranking Via Mixed Land-Use Latent Models
Mixed land use refers to the effort of putting residential, commercial and recreational uses in close proximity to one another. This can contribute economic benefits, support viable public transit, and enhance the perceived security of an area. It is naturally promising to investigate how to rank real estate from the viewpoint of diverse mixed land use, which can be reflected by the portfolio of community functions in the observed area. To that end, in this paper, we develop a geographical function ranking method, named FuncDivRank, by incorporating the functional diversity of communities into real estate appraisal. Specifically, we first design a geographic function learning model to jointly capture the correlations among estate neighborhoods, urban functions, temporal effects, and user mobility patterns. In this way we can learn latent community functions and the corresponding portfolios of estates from human mobility data and Point of Interest (POI) data. Then, we learn the estate ranking indicator by simultaneously maximizing ranking consistency and functional diversity, in a unified probabilistic optimization framework. Finally, we conduct a comprehensive evaluation with real-world data. The experimental results demonstrate the enhanced performance of the proposed method for real estate appraisal.
Y. Fu et al., "Real Estate Ranking Via Mixed Land-Use Latent Models," Proceedings of the 21st ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (2015, Sydney, Australia), pp. 299-308, Association for Computing Machinery (ACM), Aug 2015.
The definitive version is available at https://doi.org/10.1145/2783258.2783383
21st ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2015 (2015: Aug. 10-13, Sydney, Australia)
Keywords and Phrases
Data mining; Economics; Community function; Comprehensive evaluation; Economic benefits; Functional diversity; Perceived securities; Probabilistic optimization; Real estate appraisals; User mobility pattern; Land use
International Standard Book Number (ISBN)
Article - Conference proceedings
© 2015 Association for Computing Machinery (ACM), All rights reserved.
01 Aug 2015