User classification method and input method and device

Abstract

The embodiment of the invention discloses a user classification method and an input method and device. According to the embodiment, a word vector of each word in text data is calculated, a word set corresponding to each target object is determined, and feature vectors finally input into a model are determined according to the word set corresponding to each target object and the word vector corresponding to each word without relying on subjective experience of business personnel. Therefore, the training effect of the model can be improved, and the accuracy of classification or clustering according to the model can also be improved.

Description

technical field [0001] The present application relates to the field of information technology, and in particular to a method for classifying users, an input method and a device. Background technique [0002] In many business fields, it is possible to analyze and determine the characteristics of the target object, input the determined characteristics into the model for training, and obtain a classification model or clustering model, so as to facilitate subsequent classification or clustering of the target object, and finally achieve a certain business purpose. For example, a financial institution may classify users as excellent, good or poor in credit ability according to the characteristics of each target object (user), so as to determine the credit line. [0003] Usually, some features are selected in advance by business personnel based on experience (for example, in financial business scenarios, the selected features can be real estate, car ownership, education, etc.), and...

AI Technical Summary

Problems solved by technology

[0005] The embodiment of the present application provides a method for classifying users, an input method and a device to solve the problems of low accuracy and high cost of existing models for classification or clustering

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