Research and Design of Big Data Relevance Analysis System for Land Development Industry Chain

Abstract

In the land development industry chain, there are a variety of data, such as land transaction data, building sales data, developer data, etc. These data are relatively scattered, difficult to aggregate and share, unable to play the hidden value of the data. This paper presents an improved algorithm for Chinese address segmentation, and based on this algorithm, the entity linking algorithm of building and land is proposed, which correlates a large number of discrete building data with land data, and finally, the entity link algorithm is applied to the big data association analysis system as the service of the association analysis subsystem, and the analysis results are visualized through the client and server. The results show that the system can correlate a large number of isolated building and land, effectively correlate and integrate discrete data, and has good data analysis ability, which provides a strong support for enterprises and users to make decisions.