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Implicit feature extraction method and device, computer equipment and storage medium

A technology of computer equipment and hidden features, applied in computing, special data processing applications, instruments, etc., can solve the problem of low efficiency of text classification

Pending Publication Date: 2019-06-11
PING AN TECH (SHENZHEN) CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0003] The embodiment of the present application provides a hidden feature extraction method, device, computer equipment and computer-readable storage medium, which can solve the problem of relatively low text classification efficiency in traditional technologies

Method used

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  • Implicit feature extraction method and device, computer equipment and storage medium
  • Implicit feature extraction method and device, computer equipment and storage medium
  • Implicit feature extraction method and device, computer equipment and storage medium

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Embodiment Construction

[0020] The following will clearly and completely describe the technical solutions in the embodiments of the present application with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of them. Based on the embodiments in this application, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the scope of protection of this application.

[0021] It should be understood that when used in this specification and the appended claims, the terms "comprising" and "comprises" indicate the presence of described features, integers, steps, operations, elements and / or components, but do not exclude one or Presence or addition of multiple other features, integers, steps, operations, elements, components and / or collections thereof.

[0022] It should also be understood that the terminology used in the specificati...

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Abstract

The embodiment of the invention provides a hidden feature extraction method and device, computer equipment and a computer readable storage medium. The embodiment of the invention belongs to the technical field of text classification. According to the embodiment of the invention, hidden features are extracted; The method comprises the steps of obtaining a first corpus for performing hidden featureextraction, performing word embedding on the first corpus to convert the first corpus into a word vector, extracting word vector characteristics of the word vectors through a convolutional neural network; clustering description is carried out on the word vectors by adopting an unsupervised algorithm; secondly, encoding the word vector characteristics in a self-encoding mode to extract hidden characteristics of the word vector characteristics so as to realize dimension reduction processing on the data of the word vector characteristics; Therefore, hidden features of the corpora are extracted through unsupervised learning, the precision of subsequent learning modeling can be improved, and the influence of the training data amount is overcome.

Description

technical field [0001] The present application relates to the technical field of text classification, and in particular to a hidden feature extraction method, device, computer equipment and computer-readable storage medium. Background technique [0002] The traditional text classification model is a supervised learning model. The supervised learning model refers to the process of using a set of samples of known categories to adjust the parameters of the classifier to achieve the required performance. It is also called a supervised training model or a teacher learning model. Therefore, , using the supervised learning model needs to classify the text according to the samples of known categories, so when using the supervised learning model for text classification, a large amount of labeled data is required to classify the text according to the labeled data. The processing of a large amount of labeled data will lead to text classification. The efficiency is relatively low. Con...

Claims

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Application Information

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IPC IPC(8): G06F17/27G06F16/35
CPCG06F16/35G06F17/00
Inventor 金戈徐亮
Owner PING AN TECH (SHENZHEN) CO LTD
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