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- Publisher Website: 10.1109/DSAA54385.2022.10032416
- Scopus: eid_2-s2.0-85137056677
- WOS: WOS:000967751000071
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Conference Paper: PATE: Property, Amenities, Traffic and Emotions Coming Together for Real Estate Price Prediction
Title | PATE: Property, Amenities, Traffic and Emotions Coming Together for Real Estate Price Prediction |
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Authors | |
Keywords | computational social science emotion multi-source information prediction real estate regression socioeconomic characteristics traffic |
Issue Date | 13-Oct-2022 |
Abstract | Real estate prices have a significant impact on individuals, families, businesses, and governments. The general objective of real estate price prediction is to identify and exploit socioeconomic patterns arising from real estate transactions over multiple aspects, ranging from the property itself to other contributing factors. However, price prediction is a challenging multidimensional problem that involves estimating many characteristics beyond the property itself. In this paper, we use multiple sources of data to evaluate the economic contribution of different socioeconomic characteristics such as surrounding amenities, traffic conditions and social emotions. Our experiments were conducted on 28,550 houses in Beijing, China and we rank each characteristic by its importance. Since the use of multisource information improves the accuracy of predictions, the aforementioned characteristics can be an invaluable resource to assess the economic and social value of real estate. Code and data are available at: https://github.com/IndigoPurple/PATE. |
Persistent Identifier | http://hdl.handle.net/10722/333719 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Zhao, Yaping | - |
dc.contributor.author | Ravi, Ramgopal | - |
dc.contributor.author | Shi, Shuhui | - |
dc.contributor.author | Wang, Zhongrui | - |
dc.contributor.author | Lam, Edmund | - |
dc.contributor.author | Zhao, Jichang | - |
dc.date.accessioned | 2023-10-06T08:38:31Z | - |
dc.date.available | 2023-10-06T08:38:31Z | - |
dc.date.issued | 2022-10-13 | - |
dc.identifier.uri | http://hdl.handle.net/10722/333719 | - |
dc.description.abstract | <p>Real estate prices have a significant impact on individuals, families, businesses, and governments. The general objective of real estate price prediction is to identify and exploit socioeconomic patterns arising from real estate transactions over multiple aspects, ranging from the property itself to other contributing factors. However, price prediction is a challenging multidimensional problem that involves estimating many characteristics beyond the property itself. In this paper, we use multiple sources of data to evaluate the economic contribution of different socioeconomic characteristics such as surrounding amenities, traffic conditions and social emotions. Our experiments were conducted on 28,550 houses in Beijing, China and we rank each characteristic by its importance. Since the use of multisource information improves the accuracy of predictions, the aforementioned characteristics can be an invaluable resource to assess the economic and social value of real estate. Code and data are available at: https://github.com/IndigoPurple/PATE.<br></p> | - |
dc.language | eng | - |
dc.language | eng | - |
dc.relation.ispartof | 2022 IEEE 9th International Conference on Data Science and Advanced Analytics (DSAA) (13/10/2022-16/10/2022, Shenzhen, China) | - |
dc.subject | computational social science | - |
dc.subject | emotion | - |
dc.subject | multi-source information | - |
dc.subject | prediction | - |
dc.subject | real estate | - |
dc.subject | regression | - |
dc.subject | socioeconomic characteristics | - |
dc.subject | traffic | - |
dc.title | PATE: Property, Amenities, Traffic and Emotions Coming Together for Real Estate Price Prediction | - |
dc.type | Conference_Paper | - |
dc.identifier.doi | 10.1109/DSAA54385.2022.10032416 | - |
dc.identifier.scopus | eid_2-s2.0-85137056677 | - |
dc.identifier.isi | WOS:000967751000071 | - |