A Novel Scheme for Crawling and Mining of Housing Transaction Data
Luyao Chen, Tao Xu · 2021
Housing transaction data from online housing platform contains many valuable information about development trends of real estate, but is also the first-hand reference for citizens to carry out housing transaction. However, how to find the key information hidden in housing transaction data from Internet is still a serious challenge. To solve it, based on web crawling technology and visual analysis technique, this paper proposes a novel scheme for gaining and analyzing housing transaction data. It includes data crawling, data prepossessing, data analysis and other steps. An empirical research is conducted with housing transaction data of Hangzhou, China. The results show the spatial distribution characters of housing price, and the most cost-effective type of real estate in Hangzhou.