A method for optimizing site selection through big data mining

The invention provides a method for optimizing site selection through big data mining. The method comprises the following steps of S1 defining the number of stores to be deployed in a unit area as T;S2 judging whether a store exists in the subunit area or not, wherein the subunit areas are contained or belong to the unit areas, and the K subunit areas form the unit areas or part of the unit areas; if no store exists in the unit area, performing first scoring on each subunit area; If there is a store in the unit area, carrying out second scoring on each subunit area; determining the number ofsupplementary points in each supplementary point subunit area according to the second score score value and the number of supplementary point subunit areas; and S3 according to the score values of thepoint supplementing subunit areas, sequentially and circularly deploying stores in the point supplementing subunit areas from high to low. The method improves the market operation capability, continuously increases the channel