Deep Learning Error Minimizing System for Real-Time Generation of Big Data Analysis Models for Mobile App Users and Controlling Method for the Same

摘要

The present invention includes: a smartphone for transmitting basic setting information (including pattern data) input to an activated mobile app to a set path and displaying the corresponding app response signal on the mobile app; Based on the basic setting information received from the mobile app of the smartphone, the new incremental learning set and the alternative learning set that grouped the learning set preset in the DB are executed deep learning learning to calculate and store a new pattern result model in real time, and the new pattern result Deep learning error minimization system for real-time generation of big data analysis models of mobile app users including a deep learning management server that calculates an app response signal that optimally corresponds to the basic setting information of the smartphone in the model and transmits it to the corresponding smartphone and a control method thereof. Since the present invention as described above is a structure that uses the alternative learning set data generated as a representative value by grouping based on the correlation, the calculation process of deep learning learning can be significantly reduced compared to the existing pattern data learned by all deep learning. Therefore, the calculation speed is significantly improved by that amount, and accordingly, there is an effect that a pattern result model can be quickly calculated for the input pattern data.