Intelligent user portrait method based on small data input

Abstract

The invention discloses an intelligent user portrait method based on small data input, and the method comprises the steps: building a user basic information model and a behavior latitude model, inputting user corresponding data, and generating basic information behavior data; performing deep learning on the basic information behavior data to obtain user behavior high-order information data; mapping the user behavior high-order information data into a recessive internal drive model through a feedforward neural network to obtain recessive internal drive data; creating user cross-domain behaviormodel data; and matching the implicit internal drive force data with the user cross-domain behavior model data to generate a user portrait. According to the method, after earlier-stage data collectionand processing are completed, the implicit internal drive force data is matched with the user cross-domain behavior model data, and the user portrait is generated. A hidden internal drive force (BFI)technology is adopted, so that the dependence on data is greatly reduced, and small data cold start is supported; output dimensions are rich, and cross-domain prediction is supported; mitigating Maieffect.

Description

technical field [0001] The invention relates to a user portrait method, in particular to an intelligent user portrait method based on small data input. Background technique [0002] The user profiling technology in the prior art is a technology that tags users by mining user behavior data, and has many applications in interest mining, advertisement recommendation, anomaly detection, and the like. [0003] The traditional user portrait technology is mainly based on the collaborative filtering algorithm, which requires a large amount of multi-dimensional behavior data in the training process. When the user behavior data is sparse or the dimensions are sparse, the accuracy of the description of the user portrait is poor, not only It will affect commercial use, and at the same time, it will bring a lot of misleading. [0004] In addition, the traditional user portrait technology has a strong Matthew effect, and its performance on long-tail mining is very low. Therefore, suppor...

AI Technical Summary

Problems solved by technology

Its disclosed technical solution combines the Internet of Things, big data, and intelligent portrait technology, and can give professional medical advice to medical examiners. However, it collects various information of medical examiners and uses a large amount of user data to construct user portraits, which cannot solve small problems. Data cold start problem

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