Operation and maintenance project management method based on intelligent word segmentation and deep learning

A deep learning and project management technology, applied in the field of operation and maintenance project management, can solve the problems of long project application length, no way to deal with it directly, and inability to make full use of intelligent word segmentation, so as to improve production efficiency, optimize the application process, and reduce application manpower cost effect

Active Publication Date: 2020-02-28
STATE GRID CORP OF CHINA +1
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AI Technical Summary

Problems solved by technology

First: The BERT system builds vectors in units of words, which cannot make full use of the results of intelligent word segmentation; second: the BERT system is more effective for matching short sentences, but it is longer for project applications and contains more values Type (such as company output value, project budget, etc.), nominal type (such as company type, company industry, etc.) and other application scenarios, there is no way to directly deal with it

Method used

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  • Operation and maintenance project management method based on intelligent word segmentation and deep learning
  • Operation and maintenance project management method based on intelligent word segmentation and deep learning
  • Operation and maintenance project management method based on intelligent word segmentation and deep learning

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Embodiment Construction

[0046] Such as figure 1 The illustrated operation and maintenance project management method based on intelligent word segmentation and deep learning includes the following steps:

[0047] S1: Obtain special vocabulary in the field of power operation and maintenance, and construct a domain corpus in the field of power operation and maintenance according to the special vocabulary in the field of power operation and maintenance; construct a word segmenter suitable for the field of power operation and maintenance based on the field corpus and combined with the biLSTM-CRF model;

[0048] S2: Use the word segmenter to intelligently segment the application text in the project application, and extract the project application gene features of the application text according to the gene rules in the domain corpus, and then according to the project application text after word segmentation and The extracted project application gene features construct the space vector of the project application;...

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Abstract

The invention discloses an operation and maintenance project management method based on intelligent word segmentation and deep learning. The method comprises the steps of performing intelligent word segmentation on a declaration text and a declaration guide text in a project declaration according to a domain corpus biLSTM-CRF model; constructing a project declaration form space vector and a project declaration guide space vector; calculating a similarity value between a project declaration form space vector and a project declaration guide space vector through a convolutional neural network enhanced by an attention mechanism; finally, judging whether the project declaration passes automatic review or not through the similarity value. The project declaration process can be optimized, the project declaration period can be shortened, meanwhile, the declaration labor cost can be reduced, and the production efficiency can be improved.

Description

Technical field [0001] The invention relates to an operation and maintenance project management method based on intelligent word segmentation and deep learning. Background technique [0002] After Hinton et al. proposed deep learning in 2006, artificial neural networks began to gain attention in the field of natural language processing. At present, some results have been achieved in the application of natural language processing in combination with deep learning models. [0003] Language model is the first natural language processing problem to be studied using neural networks. In 2003, Bengio et al. proposed a word vector (Word embedding) method, which can transform the word mapping into an independent vector space; further combined with a nonlinear neural network to propose an N-Gram model; inspired by this, Collobert et al. based on the word vector method and Multi-layer one-dimensional convolutional neural network (Convolutional neural network, CNN), realizes a SENNA (Semantic...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F40/284G06N3/04G06N3/08
CPCG06N3/08G06N3/045
Inventor 王文娟戴诚卓灵王吉哲龚黎慧倩彭云竹赵中璇陈聿
Owner STATE GRID CORP OF CHINA
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