Text classification method, system, readable storage medium and electronic device

A text classification and text technology, applied in the field of data processing, can solve the problem of not making full use of sentence structure, and not being able to apply unrestricted phrase structure trees well.

Active Publication Date: 2020-10-20
SHENZHEN GRADUATE SCHOOL TSINGHUA UNIV
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Problems solved by technology

Obviously, the existing models do not make full use of the sentence structure, or are not suitable for unrestricted phrase structure trees

Method used

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  • Text classification method, system, readable storage medium and electronic device
  • Text classification method, system, readable storage medium and electronic device
  • Text classification method, system, readable storage medium and electronic device

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Embodiment approach

[0069] Please refer to figure 1 , a preferred embodiment of the text classification method of the present invention includes the following steps:

[0070] Step S100, acquiring the phrase structure tree of the corresponding sentence text.

[0071] In this embodiment, the sentence text can be obtained first, and the corresponding phrase structure tree can be generated through an existing algorithm (such as the algorithm provided by Stanford Parser). It can be understood that the obtained sentence text can be obtained through a third-party platform, for example, the corresponding sentence text can be input on the third-party platform to generate a corresponding phrase structure tree.

[0072] Understandably, the user can also directly obtain the phrase structure tree corresponding to the sentence text from a third-party data set (such as the SST data set). For example, see figure 2 , the phrase structure tree of the sentence text "You won't like Rogers, but you will quickly r...

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Abstract

A text classification method, system, readable storage medium, and electronic equipment include: taking a phrase structure tree corresponding to a sentence text, wherein the sentence text includes one or more tags, each tag corresponds to a word vector, and each word vector Used as the input of the leaf node in the phrase structure tree; the first operation process is performed on the leaf node in the phrase structure tree by a mark encoder, so that the word vector of the sentence text is converted into a corresponding sentence vector; The internal node in the phrase structure tree executes the second operation process to obtain the output of the root node in the phrase structure tree according to the sentence vector; the classifier is trained according to the output of the root node. The invention can improve the accuracy rate of text classification.

Description

technical field [0001] The invention relates to the field of data processing, in particular to a neural network-based text classification method, system, readable storage medium and electronic equipment. Background technique [0002] Most neural networks used for sentence representation usually fall into one of the following categories: sequential models, convolutional models, and recurrent models. Recently, sequence models have witnessed widespread applications in Natural Language Processing (NLP), such as text classification, machine translation, question answering, etc. In these methods, a Recurrent Neural Network (RNN) takes each word as input, aggregates the word with its previous state, and finally outputs its result for an entire sentence. The synthesized results as fixed-length vectors contain rich semantic information and are used in subsequent NLP tasks. [0003] However, in natural language understanding, recurrent neural networks including LSTMs all process wor...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F16/35G06N3/04
CPCG06N3/045
Inventor 袁春程洲马志明
Owner SHENZHEN GRADUATE SCHOOL TSINGHUA UNIV
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