Academic literature on the topic 'Real Estate Data'

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Journal articles on the topic "Real Estate Data"

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Kim, Jin. "Research on Real Estate Needs Using Big Data." Korea Real Estate Society 76 (June 30, 2025): 119–37. https://doi.org/10.37407/kres.2024.43.2.119.

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Recognizes that the rapidly changing, social structure and accelerating technological advancements— particularly digital transformation—are bringing significant changes to the, real estate market. Changes in consumer lifestyles and the diversification of values have had complex effects on the needs for residential and commercial, spaces. Accordingly, methods for analyzing real estate demand are becoming increasingly sophisticated. Against this backdrop, the study sought to systematically analyze the needs, of modern real estate consumers through big data and to quantitatively identify shifts i
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Schernthanner, Harald, Hartmut Asche, Julia Gonschorek, and Lasse Scheele. "Spatial Modeling and Geovisualization of Rental Prices for Real Estate portals." International Journal of Agricultural and Environmental Information Systems 8, no. 2 (2017): 78–91. http://dx.doi.org/10.4018/ijaeis.2017040106.

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From a geoinformation science perspective real estate portals apply non-spatial methods to analyse and visualise rental price data. Their approach shows considerable shortcomings. Portal operators neglect real estate agents' mantra that exactly three things are important in real estates: location, location and location (Stroisch, 2010). Although real estate portals retacord the spatial reference of their listed apartments, geocoded address data is used insufficiently for analyses and visualisation, and in many cases the data is just used to “pin” map the listings. To date geoinformation scienc
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Cajias, Marcelo, and Anett Wins. "Data intelligence and real estate – machines are the real game changer." Journal of Property Investment & Finance 40, no. 3 (2021): 306–10. http://dx.doi.org/10.1108/jpif-11-2021-0101.

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PurposeThe paper shows with two concrete examples about how algorithms are used in active real estate management. The paper also highlights that the discussion about the adoption of new technologies is crucial for market players.Design/methodology/approach The authors review the current status quo about new technologies in real estate and provide two examples of how algorithms can be used to understand locations and the value drivers of rents.FindingsLocation, location, location is nowadays data, data, data coupled with the knowledge of how to create life out of data. Algorithm can help to und
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KIRICHEK, Yu O. "CADASTRAL REGISTRATION OF REAL PROPERTY WITH DATA DIGITALIZATION." Ukrainian Journal of Civil Engineering and Architecture, no. 5 (December 27, 2021): 50–55. http://dx.doi.org/10.30838/j.bpsacea.2312.261021.50.800.

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Problem statement. The transition in Ukraine from registration and accounting of land in the State Land Cadastre to registration and accounting of real estate in the multi-purpose cadastre requires research aimed at optimizing the information of the multi-purpose cadastre and the form of data representation based on their digitalization to limit the size of the database by technological support. The composition and scope of real estate accounting information data determine the purpose and functions of the multi-purpose cadastre. The problem is the huge amount of information about real estate a
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Sinenko, V. "Classification of errors in details Single roster of real estate in verification of data." Bulletin of Science and Practice 4, no. 10 (2018): 384–90. https://doi.org/10.5281/zenodo.1462019.

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In connection with the entry in 2017 of the Federal Law of July 13, 2015 no. 218-FZ. On state registration of real estate, one of the priority and important tasks in the registration and registration system is the mechanism for correcting errors contained in the real estate cadastre. In practice, the presence of errors in the register of real estate remains the most urgent and global problem, requiring an immediate decision to identify and correct. The investigated problem is the inconsistency and duplication of the information of the real estate cadastre system and the Unified State Regi
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Ersoz, Filiz, Taner Ersoz, and Muhammet Soydan. "Research on Factors Affecting Real Estate Values by Data Mining." Baltic Journal of Real Estate Economics and Construction Management 6, no. 1 (2018): 220–39. http://dx.doi.org/10.2478/bjreecm-2018-0017.

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Abstract Construction sector has an important place in Turkey’s economy. Real estate sales for the sector are increasing in parallel. However, the purchase cost is also important for those who are willing to buy a real estate. In the acquisition of real estate, factors such as size, location and age of the house are taken into consideration. The aim of the article is to conduct research on factors affecting real estate values by data mining. In this study, the most important variables that determine the value of the real estate have been investigated by data mining methods. The research has be
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Chen, C. X., H. Zhang, K. Jiang, et al. "RESEARCH ON EVALUATION METHOD OF REAL ESTATE REGISTRATION DATA QUALITY." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B3-2021 (June 29, 2021): 749–54. http://dx.doi.org/10.5194/isprs-archives-xliii-b3-2021-749-2021.

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Abstract. In recent years, China has promulgated the "Civil Code of the People's Republic of China", "Implementation Rules of the Provisional Regulations on Real Estate Registration" and other laws and regulations, which have protected citizens' rights and obligations in real estate from the legal system. It shows that the quality of real estate registration data is very important. At present, there is no set of standards for evaluating the quality of real estate registration data. This article sorts out the production process of real estate registration data and focuses on the four stages of
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Conover, C. Mitchell, Joseph D. Farizo, H. Swint Friday, and David S. North. "The Diversification Benefits of Foreign Real Estate: Evidence from 40 Years of Data." Journal of Risk and Financial Management 17, no. 4 (2024): 160. http://dx.doi.org/10.3390/jrfm17040160.

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We investigate the potential of global real estate to improve the long-term performance of a US equity portfolio, utilizing a recent dataset of 40 years’ worth of US stocks, US real estate, 13 foreign stock markets, and 13 foreign real estate markets across diverse regions. Despite a modest performance in terms of risk and return, foreign real estate has consistently lower correlations with US stocks compared to foreign equities. Rolling correlation analysis indicates that foreign real estate markets remain relatively segmented compared to foreign equity, despite increasing financial market co
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Ashok, Dasari. "Estimating the Price of Real Estate Properties with the Help of Online Images." ECS Transactions 107, no. 1 (2022): 16933–41. http://dx.doi.org/10.1149/10701.16933ecst.

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When it comes to property investment pricing, it may be tough for homebuyers to understand and compare. A number of estate evaluation methods have been developed in order to analyze real estate, however they are constrained by the traditional data sources for estate assessment. Potential exists, however, to collect and analyze property-related mobile data when new ways of doing things arise. Use estates' geographical dependency to increase the value of a property. The New York Times reports that a property's value may be determined by its own characteristics, the value of neighboring homes in
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Sun, Ziyang. "Research on Product Decision of Real Estate Project Based on Big Data Analysis." Frontiers in Business, Economics and Management 11, no. 2 (2023): 220–23. http://dx.doi.org/10.54097/fbem.v11i2.12593.

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The characteristics of product decision-making of real estate projects are determined by the particularity of real estate projects. Because the development and construction period of real estate projects is long, the investment is large, many parties participate, there are many risk factors in the development process, and after the development is completed, it is unrepeatable, and most of them aim at profit. Real estate regulation and control is a long-term work, and it is urgent to establish a set of operational analysis and decision support platform that runs through the whole chain of real
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Dissertations / Theses on the topic "Real Estate Data"

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Park, Sun Jung Park S. M. Massachusetts Institute of Technology. "Data science strategies for real estate development." Thesis, Massachusetts Institute of Technology, 2020. https://hdl.handle.net/1721.1/129099.

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Thesis: S.M. in Real Estate Development, Massachusetts Institute of Technology, Program in Real Estate Development in conjunction with the Center for Real Estate, September, 2020<br>Cataloged from student-submitted PDF of thesis.<br>Includes bibliographical references (pages 43-45).<br>Big data and the increasing usage of data science is changing the way the real estate industry is functioning. From pricing estimates and valuation to marketing and leasing, the power of predictive analytics is improving the business processes and presenting new ways of operating. The field of affordable housing
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Bennion, Laird. "Identifying data center supply and demand." Thesis, Massachusetts Institute of Technology, 2016. http://hdl.handle.net/1721.1/103457.

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Thesis: S.M. in Real Estate Development, Massachusetts Institute of Technology, Program in Real Estate Development in conjunction with the Center for Real Estate, 2016.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 66-69).<br>This thesis documents new methods for gauging supply and demand of data center capacity and addresses issues surrounding potential threats to data center demand. This document is divided between a primer on the composition and engineering of a current data center, discussion of issues surrounding data center demand, Moore's Law and
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Mao, Chiu-dik William, and 毛照逖. "Real estate geographic information systems (GIS) for urban redevelopment through the perspective of a real estate developer." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2003. http://hub.hku.hk/bib/B27050270.

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Callahan, Mark F. (Mark Francis). "Using transactional and spatial data to determine drivers of industrial land value." Thesis, Massachusetts Institute of Technology, 2017. http://hdl.handle.net/1721.1/113483.

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Thesis: S.M. in Real Estate Development, Massachusetts Institute of Technology, Program in Real Estate Development in conjunction with the Center for Real Estate, 2017<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 74-76).<br>The value of a given parcel of land is determined by a multitude of factors based on its location and physical characteristics. No two parcels are alike, making direct comparison between parcels and the study of underlying land values difficult. Further, in locations where land is most valuable, there are often existing improvements
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Jones, Ryan Hunter. "Risk and return in institutional commercial real estate : a fresh look with new data." Thesis, Massachusetts Institute of Technology, 2012. http://hdl.handle.net/1721.1/77123.

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Thesis (S.M. in Real Estate Development)--Massachusetts Institute of Technology, Program in Real Estate Development in Conjunction with the Center for Real Estate, 2012.<br>"September 2012." Cataloged from department-submitted PDF version of thesis. This electronic version was submitted and approved by the author's academic department as part of an electronic thesis pilot project. The certified thesis is available in the Institute Archives and Special Collections.<br>Includes bibliographical references (p. 82-84).<br>Commercial Real Estate is a large asset class, increasingly owned by professi
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Owusu-Opoku, Peter K. "Commercial real estate operating expenses : an analysis of office operating expenses using NCREIF property level data." Thesis, Massachusetts Institute of Technology, 2015. http://hdl.handle.net/1721.1/101323.

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Thesis: S.M. in Real Estate Development, Massachusetts Institute of Technology, Program in Real Estate Development in conjunction with the Center for Real Estate, 2015.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (page 54).<br>How do the various categories of operating expenses for institutional grade office buildings vary with changes in rental income and occupancy? The general consensus held is that, following the linear relationship that exists between variable expenses, occupancy and income; a change in either occupancy or income would result in a change
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Råhlén, Oskar, and Sacharias Sjöqvist. "Image Classification of Real Estate Images with Transfer Learning." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-259759.

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Each minute, over 2 000 searches are made on Sweden’s largest real estate website. The site has over 20 000 apartments for sale in the Stockholm region alone. This makes the search-function a vital tool for the users to find their dream apartment, and thus the quality of the search-function is of significance. As of today, it’s only possible to filter and sort by meta-data such as number of rooms, living area, price, and location, but not on more complex attributes, such as balcony or fireplace. To prevent the need for manual categorization of objects on the market, one option could be to use
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Kass, Hunter L. (Hunter Lindsay). "The luxury second home market : an analysis of historical sales and property data at The Greenbrier Resort (White Sulphur Springs, WV)." Thesis, Massachusetts Institute of Technology, 2011. http://hdl.handle.net/1721.1/68185.

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Thesis (S.M. in Real Estate Development)--Massachusetts Institute of Technology, Program in Real Estate Development in Conjunction with the Center for Real Estate, 2011.<br>This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.<br>Cataloged from student-submitted PDF version of thesis.<br>Includes bibliographical references (p. 54-55).<br>The global economic expansion and subsequent creation of wealth as well as increased purchasing power and disposable income has contributed to the growth in the second
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Huh, Keun S. M. Massachusetts Institute of Technology. "Asian real estate investment : data utilization for the decision making process." Thesis, Massachusetts Institute of Technology, 2007. http://hdl.handle.net/1721.1/42020.

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Thesis (S.M. in Real Estate Development)--Massachusetts Institute of Technology, Dept. of Urban Studies and Planning, 2007.<br>This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.<br>Includes bibliographical references (leaf 38).<br>Many investors in developed countries believe the Asian emerging market to be highly risky due to numerous uncertainties including limited market information to make sound investment decisions. However, still successful investment deals were completed by many investors who
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Nilsson, Pontus. "Prediction of residential real estate selling prices using neural networks." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-249637.

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With the rising housing prices of the last 20 years, the appraisal of real estate has become more difficult. Underlined by the large differences between listing and selling prices, the valuation process brings a level of uncertainty. With the advances within the field of machine learning in recent years, attempts have been made to apply these techniques to the real estate market. This thesis investigates the potential of using neural networks to predict selling prices of apartments in Stockholm, based on apartment parameters. Networks are trained to either make an improved valuation, based on
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Books on the topic "Real Estate Data"

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M, Clapp John, ed. Data sources for real estate decisions. Center for Real Estate and Urban Economic Studies, School of Business Administration, University of Connecticut, 1985.

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Nelson, Theron R. Real estate software package. Prentice Hall, 1990.

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Crumbley, Tony L. Commercial real estate surveys. American Chamber of Commerce Researchers Assoc., 1988.

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Robert, Irwin. Computerizing your real estate office. McGraw-Hill, 1985.

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John, Jones. Farm real estate historical series data, 1950. U.S. Dept. of Agriculture, Economic Research Service, 1985.

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Culbertson, Ed. Computer applications for real estate. Thomson/South-Western, 2005.

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Camerrer, Ron. The complete real estate computer workbook. Institute for Business Planning, 1986.

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John, Jones. Farm real estate historical series data, 1950-92. U.S. Dept. of Agriculture, Economic Research Service, 1993.

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John, Jones. Farm real estate: Historical series data, 1950-92. U.S. Dept. of Agriculture, Economic Research Service, 1993.

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United States. Dept. of Agriculture. Economic Research Service., ed. Farm real estate: Historical series data, 1950-85. U.S. Dept. of Agriculture, Economic Research Service, 1985.

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Book chapters on the topic "Real Estate Data"

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Tsolacos, Sotiris, and Mark Andrew. "Real estate data." In Applied Quantitative Analysis for Real Estate. Routledge, 2020. http://dx.doi.org/10.1201/9780203710876-2.

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Winson-Geideman, Kimberly, Andy Krause, Clifford A. Lipscomb, and Nicholas Evangelopoulos. "Traditional real estate data." In Real Estate Analysis in the Information Age. Routledge, 2017. http://dx.doi.org/10.4324/9781315311135-1.

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Winson-Geideman, Kimberly, Andy Krause, Clifford A. Lipscomb, and Nicholas Evangelopoulos. "Gathering real estate data." In Real Estate Analysis in the Information Age. Routledge, 2017. http://dx.doi.org/10.4324/9781315311135-5.

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Kingaby, Simon A. "The Real Estate API." In Data-Driven Alexa Skills. Apress, 2021. http://dx.doi.org/10.1007/978-1-4842-7449-1_15.

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Hazeem, Hamad, and Ebrahim AlBurshaid. "Fragmented Data Landscape and Data Asymmetries in the Real Estate Industry." In Blockchain in Real Estate. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-99-8533-3_10.

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Michel, Gaston. "Data." In Real Estate Risk in Equity Returns. Gabler, 2009. http://dx.doi.org/10.1007/978-3-8349-9496-7_4.

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Daithankar, Jayant. "Master Data Objects." In SAP Flexible Real Estate Management. Apress, 2016. http://dx.doi.org/10.1007/978-1-4842-1482-4_2.

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Dong, Huijian. "Data Analytics in Real Estate." In Data Analytics in Finance. Auerbach Publications, 2025. https://doi.org/10.1201/9781003620198-10.

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Schlundt, Maik, Thomas Bender, Nancy Bock, et al. "Data Management and Data Exchange for BIM and FM." In BIM in Real Estate Operations. Springer Fachmedien Wiesbaden, 2023. http://dx.doi.org/10.1007/978-3-658-40830-5_5.

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Voigtländer, Michael. "Real Estate Data Sources in Germany." In Understanding German Real Estate Markets. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-23611-2_1.

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Conference papers on the topic "Real Estate Data"

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Guo, Guihai, and Lihui Jin. "Organization of real estate spatiotemporal data." In 2010 International Conference on Computer Application and System Modeling (ICCASM 2010). IEEE, 2010. http://dx.doi.org/10.1109/iccasm.2010.5620317.

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Cajias, Marcelo. "New Technology and Data in Real Estate." In 26th Annual European Real Estate Society Conference. European Real Estate Society, 2019. http://dx.doi.org/10.15396/eres2019_155.

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Edet, Theresa. "Investigating the application of Data and Data Analytics in Real Estate Investment Decisions Among Lagos Valuers." In 22nd African Real Estate Society Conference. African Real Estate Society, 2023. http://dx.doi.org/10.15396/afres2023-046.

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"Data Dilemmas in European Real Estate Markets." In 14th Annual European Real Estate Society Conference: ERES Conference 2007. ERES, 2007. http://dx.doi.org/10.15396/eres2007_250.

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Nappi-Choulet, Ingrid, and Gisele Ribeiro. "New Technology and New Data in Real Estate." In 25th Annual European Real Estate Society Conference. European Real Estate Society, 2018. http://dx.doi.org/10.15396/eres2018_86.

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Stoyanov, Ivaylo, Rui Mendes, Jose Ramon, et al. "New Technology and Data in Real Estate Education." In 26th Annual European Real Estate Society Conference. European Real Estate Society, 2019. http://dx.doi.org/10.15396/eres2019_142.

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Bekkerman, Ron, Vanja Josifovski, and Foster Provost. "Data Science for the Real Estate Industry." In KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. ACM, 2020. http://dx.doi.org/10.1145/3394486.3406476.

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Hu, Yidong, Fenglei Mei, Chenling Pan, and Tao Nie. "Spatiotemporal Data Mining of Real Estate Registration." In Proceedings of the 4th International Conference on Economic Management and Big Data Applications, ICEMBDA 2023, October 27–29, 2023, Tianjin, China. EAI, 2024. http://dx.doi.org/10.4108/eai.27-10-2023.2341903.

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Zhao, Yun, Girija Chetty, and Dat Tran. "Deep Learning for Real Estate Trading." In 2022 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE). IEEE, 2022. http://dx.doi.org/10.1109/csde56538.2022.10089222.

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Tan, Fei, Chaoran Cheng, and Zhi Wei. "Modeling Real Estate for School District Identification." In 2016 IEEE 16th International Conference on Data Mining (ICDM). IEEE, 2016. http://dx.doi.org/10.1109/icdm.2016.0164.

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Reports on the topic "Real Estate Data"

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Dove, Linda P., Mark R. Graves, and Evelyn Lopez. GIS-Assisted Spatial Data Management for Corps of Engineers Real Estate Activities. Defense Technical Information Center, 2001. http://dx.doi.org/10.21236/ada397425.

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Jha, Deepika, Manish Dubey, and Sejal Singla. The State of Real Estate Regulation in India 2023. Indian Institute for Human Settlements, 2023. http://dx.doi.org/10.24943/tsreri11.2023.

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The RERA Act received widespread acclaim for its objectives to regulate a sizable and mostly unregulated sector marked by significant consumer investment and grievances. Seven years after the RERA Act, this report draws on data available in the public domain from 18 RERAs and their websites to take stock of the progress made in relation to the remit of RERA activity, the extent and timeliness of project disclosures, arrangements for grievance redress and institutional functioning of real estate regulatory authorities.
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Dove, Linda P. GIS-Assisted Spatial Data Management for Corps of Engineers Real Estate Activities: Spatial Data Conversion Options. Defense Technical Information Center, 2002. http://dx.doi.org/10.21236/ada409099.

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Klug, Victoria, Brett Singer, Tod Bedrosian, and Chris DCruz. CHARACTERISTICS OF RANGE HOODS IN CALIFORNIA HOMES DATA COLLECTED FROM A REAL ESTATE WEB SITE. Office of Scientific and Technical Information (OSTI), 2011. http://dx.doi.org/10.2172/1051043.

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Spencer, Nekeisha. Extreme Weather and Real Estate: A Case Study of the Jamaican Housing Market. Inter-American Development Bank, 2023. http://dx.doi.org/10.18235/0004984.

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The damaging effects of extreme weather on residential real estate are concerning for many countries around the world. Results from combining hurricane and rainfall events with 16 years of data on sale prices of land, apartments and the value of mortgages across different localities in Jamaica reveal that the housing market should take urgent adaptation measures. While hurricanes play a role in reducing apartment prices, they do not affect residential housing prices and the value of existing mortgages. The study also demonstrates that extreme rainfall reduces the value of new mortgages. The re
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Cruces, Juan José. Argentina's Residential Real Estate Sector: A Magnet for Savings amidst Mistrust in Traditional Investment Vehicles. Inter-American Development Bank, 2016. http://dx.doi.org/10.18235/0009277.

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This paper measures the flow of funds into the real estate sector for the city of Buenos Aires since 1992 and compares it to traditional savings instruments. For each dollar that went into the city's real estate from 1992 until 2000, about six dollars went into deposits in the national banking system. From 2003 until 2012, for each dollar that went into real estate, only 99 cents went to bank deposits. While the 2010 census reports a vacancy rate of 24 percent for the city, analysis of a micro data set on individual house electricity consumption suggests that the rate is only about 6 percent,
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Cloutier, Deborah, Farshid Hosseini, and Andrew White. Utilizing Commercial Real Estate Owner and Investor Data to Analyze the Financial Performance of Energy Efficient, High-Performance Office Buildings. Office of Scientific and Technical Information (OSTI), 2017. http://dx.doi.org/10.2172/1419623.

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Subedi, Dipak, and Anil K. Giri. Debt use by U.S. farm businesses, 2012-2021. Economic Research Service, U.S. Department of Agriculture, 2024. http://dx.doi.org/10.32747/2024.8478364.ers.

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The short-term Federal funds rate, which impacts the interest rate of other loans, has been increasing since March 2022. The rate can disproportionately affect demand for different types of loans, as well as the choice of the lender for different farm sizes. This report examines farm debt by lenders, as well as other attributes, such as the use of different loan types (real estate and non-real estate) among different types of farm businesses. The authors used data from multiple sources, including the USDA, Economic Research Service's Farm Income and Wealth Statistics and Agricultural Resource
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Rojas, Eduardo. Monitoring Urban Markets: The Experience of Latin American Cities. Inter-American Development Bank, 1997. http://dx.doi.org/10.18235/0008951.

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This Urban Sector present Dissemination Note reports on the presentations made and discussions held in the Seminar organized by the Lincoln Institute of Land Policy of Cambridge, MA, on the Latin American experience in monitoring urban land markets. The Seminar gathered 10 representatives of private firms that, as part of their business, systematically gather data and sale information about urban real estate markets. Systematic information about urban land and real estate transactions play a significant role in improving the operation of urban markets. Further, this information is a valuable i
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Cumberbatch, Janice, Fabian Hinds, Leonardo Corral, et al. The Impact of Coastal Infrastructure Improvements on Economic Growth: Evidence from Barbados. Inter-American Development Bank, 2016. http://dx.doi.org/10.18235/0011763.

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This paper presents the first rigorous impact evaluation of a shoreline stabilization program in Barbados and attempts to assess whether shoreline stabilization investments indeed have beneficial effects on medium-term economic growth in Small Island Developing States through stimulating tourism demand and real estate development. The analysis relies on a carefully designed geographic information systems (GIS) dataset, which comprises extensive panel data from Barbados' touristic West and South Coasts on key infrastructure, beach characteristics, and real estate activity, as well as remotely-s
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