Analysis and Utilization of Housing Information based on Open API and Web Scraping

초록

In an era of low interest rates around the world, interest in real estate has increased. We can collect real estate information using the Internet, but it takes a lot of time to find. In this paper, real estate information from January 2015 to April 2024 is collected from three places to help users more easily collect real estate information of interest and use it for sales. First, by analyzing HTML documents using web scraping techniques, information on real estate of interest is automatically extracted from the website of the platform company. Second, the actual transaction price of the real estate is additionally collected through the open API provided by the Ministry of Land, Infrastructure and Transport. Third, real estate-related news is provided so that users can learn about the future value and prospects of real estate. The simulation results for the data collected in this study show that the lowest price predicted by the ARIMA model is expected to be in May 2024 among the next eight months. Therefore, by following this procedure, real estate buyers can make more efficient home sales by referring to related information including the predicted transaction price.

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