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Intelligent administrative law enforcement case information extraction and cause affirmation method

An information extraction and administrative technology, applied in the field of legal artificial intelligence, can solve the problems of low efficiency of information extraction, inability of entities to use further, and low accuracy rate, so as to reduce time resources and computing resources, reduce dependence on data volume, and improve accuracy sexual effect

Pending Publication Date: 2022-05-27
SHANDONG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0008] In order to solve the problems of low efficiency and accuracy in the information extraction of administrative penalty decision documents in the existing judicial field, and the extracted entities cannot be used further, the present invention proposes an information extraction method for administrative penalty decision documents. After the long text is extracted, it is used as input to further generate a short text format that meets the current mainstream NLP tasks.

Method used

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  • Intelligent administrative law enforcement case information extraction and cause affirmation method
  • Intelligent administrative law enforcement case information extraction and cause affirmation method
  • Intelligent administrative law enforcement case information extraction and cause affirmation method

Examples

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Effect test

Embodiment 1

[0091] An intelligent administrative law enforcement case information extraction and cause of action identification method, such as Figure 7 shown, including the following steps:

[0092] like figure 1 As shown, the model training process includes steps A to E;

[0093] A. Data set construction: crawl the administrative penalty decision from the website, extract the text content tagged with html, and mark the short text in the text content;

[0094] B. Corpus conversion:

[0095] Divide all long sentences in administrative law enforcement documents into short sentences according to punctuation;

[0096] The short text marked in the data set of step A is divided into sentences according to punctuation;

[0097] Find the longest short sentence in the short text, use the longest short sentence as the standard, find out the sentence similar to the longest short sentence from the administrative penalty document, extract and save, and execute recursively until all the sentences...

Embodiment 2

[0109] According to a kind of intelligent administrative law enforcement case information extraction and cause of action determination method described in Embodiment 1, the difference is:

[0110] Further preferably, in step A, marking the text content refers to: extracting all required key fields from the administrative law enforcement documents, and recombining them into a new short text only including key purpose information according to the semantics; These short texts are marked in the penalty documents.

[0111] Specifically, the administrative penalty decision letter is obtained by crawling from the administrative penalty document website, and the text content labeled as html is extracted. After that, the text content is annotated, which specifically refers to: manually extracting important information in the text, combining the information according to the semantics, adding appropriate associated words and modifying the sentence order. The result of the annotation is t...

Embodiment 3

[0157] A computer device includes a memory and a processor, the memory stores a computer program, and when the processor executes the computer program, the processor implements the steps of the intelligent administrative law enforcement case information extraction and case cause determination method described in Embodiment 1 or 2.

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Abstract

The invention relates to an intelligent administrative law enforcement case information extraction and cause affirmation method. The method comprises the following steps: A, constructing a data set; c, preprocessing and vectorizing extracted data; D, training an extraction model based on a DGCNN; E, generating a short text based on UniLM, and training a generation model; f, inputting a law enforcement document text for prediction: processing an administrative law enforcement document needing to be converted through the steps A to C, inputting an obtained processing result into the trained extraction model, generating an extraction result, storing the extraction result, and further inputting the extraction result into the trained generation model to obtain a short text suitable for analysis of other downstream tasks. According to the method, the DGCNN is adopted as an extraction model, and the information of the text data is extracted by using the non-serialized neural network structure characteristics, so that the consumed time resources and computing resources are greatly reduced, and the extraction accuracy is improved.

Description

technical field [0001] The invention relates to an intelligent administrative law enforcement case information extraction and cause of action determination method, which belongs to the technical field of legal artificial intelligence. Background technique [0002] With the continuous development of my country's legal system, legal documents are becoming more and more perfect, and more detailed regulations have been made on the format and content of legal documents, and the theoretical research work on legal documents has also made great progress. Therefore, legal documents more standardized and complete. With the continuous advancement of information technology, there are a large number of administrative law enforcement documents resources on the Internet. As an important carrier of legal judgments and information, administrative law enforcement documents contain a large amount of available information. If the information can be extracted and used correctly, it will save a ...

Claims

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Application Information

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IPC IPC(8): G06F16/31G06F16/35G06F16/34G06F40/295G06F40/30G06N3/04G06N3/08G06Q50/18
CPCG06F16/313G06F16/35G06F16/345G06F40/295G06F40/30G06N3/08G06Q50/18G06N3/048G06N3/045
Inventor 贲晛烨冯晓炜李玉军周莹孙浩谢霆轩
Owner SHANDONG UNIV
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