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Abstract

Disclosed is a method of predicting crime occurrence in a prediction target region using big data, the method including: collecting crime prediction data of the prediction target region from a plurality of data domains; collecting crime occurrence data of crime that occurred in the prediction target region during a preset period of time from a crime occurrence record domain; analyzing the crime prediction data and the crime occurrence data of each of the data domains according to a statistical analysis, and extracting meaningful data of the crime prediction data as available data by each of the data domains; and predicting crime occurrence by applying the available data to a pre-registered deep learning algorithm, wherein the available data is classified into a plurality of data groups according to a data type, and the deep learning algorithm includes: a first deep neural network; a second deep neural network; and an output.

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First Claim