User movement behavior prediction method and device based on multi-granularity neural network

Abstract

The invention discloses a user movement behavior prediction method, device and equipment based on a multi-granularity neural network and a computer readable storage medium, and the method comprises the steps: mapping a prediction space of a user movement position to a map, and obtaining a map region corresponding to the prediction space; respectively dividing the map area according to different granularities, and respectively converting the current movement track of the user into a plurality of grid ID sequences corresponding to the different granularities under the different granularities; using a multi-granularity neural network model; and respectively predicting the plurality of grid ID sequences by using different prediction models under the different granularities to obtain a plurality of prediction results of the user moving position under the different granularities, and fusing the plurality of prediction results to obtain a target prediction result of the user moving position.According to the method, the device, the equipment and the computer readable storage medium provided by the invention, the accuracy of predicting the movement behavior of the user is improved.

Description

Technical field [0001] The present invention relates to the technical field of user behavior prediction, and in particular to a method, device, equipment and computer-readable storage medium for user movement behavior prediction based on a multi-granular neural network. Background technique [0002] With the widespread use of smart phones and the rapid development of car navigation systems, they have become part of people's daily lives. This has led to the popularization of embedded GPS devices and the rapid development of positioning technology. We are also benefiting more and more from various types of location-based services (LBS). The user's movement behavior prediction is to predict the user's possible movement position in the future after a part of the user's sub-trajectory is given. A large number of LBS systems rely on the prediction of the user's mobile behavior, such as recommending users' attractions and advertisements, real-time traffic flow analysis, and automatical...

AI Technical Summary

Problems solved by technology

[0007] The purpose of the present invention is to provide a user mobile behavior prediction method, device, equipment and computer-readable storage medium based on a multi-granularity neural network to solve the problem of low prediction accuracy of traditional user mobile behavior prediction algorithms

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