Intelligent user portrait method based on small data input

Abstract

The invention discloses an intelligent user portrait method based on small data input, which includes: creating 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, Obtain the high-level information data of user behavior; map the high-level information data of user behavior to the implicit internal driving force model through the feedforward neural network, and obtain the implicit internal driving force data; create user cross-domain behavior model data; Drive data is matched with user cross-domain behavior model data to generate user portraits. After completing the previous data collection and processing, the present invention matches the hidden internal drive data with the user's cross-domain behavior model data to generate a user portrait. The implicit internal driving force (BFI) technology is adopted, which greatly reduces the dependence on data and supports cold start of small data; the output dimension is rich and supports cross-field prediction; the Matthew effect is weakened.

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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