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Question matching method in electric power intelligent question-answering system

A technology of intelligent question answering and matching methods, applied in the field of information processing, can solve problems such as long time and complex reasoning process, and achieve the effect of improving accuracy

Inactive Publication Date: 2020-12-25
JIANGSU ELECTRIC POWER INFORMATION TECH
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Problems solved by technology

This method can improve the accuracy of answering user questions, but there are problems such as complex reasoning process and long time

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[0030] A question matching method in an electric power intelligent question answering system based on the G-BI-LSTM model, figure 1 It is a block diagram of the principle of the question matching method of the present invention, including: at first performing zero padding or truncating operations on the query question P entered by the user and the question Q in the system knowledge base, so that the sentence sequence becomes a fixed length; then through the GloVe model Generate the word vector corresponding to the word in the sentence sequence; then input the word vector into the BI-LSTM model to obtain the word vector with contextual meaning; on this basis, use the convolutional neural network to extract the word vector feature to obtain the sentence Feature vectors, and further extract common features from the feature vectors; finally, splice the feature vectors and common feature vectors of question P and question Q, and input them into the fully connected layer to obtain si...

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Abstract

The invention discloses a question matching method in an electric power intelligent question-answering system. The method comprises the following steps: firstly, carrying out zero filling or truncation operation on a query question P input by a user and a question Q in a system knowledge base to enable a sentence sequence to be changed into a fixed length; generating a corresponding word vector inthe sentence sequence through a GloVe model; inputting the word vector into a BILSTM model to obtain a word vector with context meaning; on the basis, extracting word vector features by using a convolutional neural network to obtain feature vectors of sentences, and further extracting common features from the feature vectors; and finally, splicing the feature vectors of the question P and the question Q and the common feature vector, and inputting the spliced feature vectors into a full connection layer to obtain a similarity prediction result. According to the method, deep learning is applied to the field of electric power intelligent questions and answers, the context of sentence words can be effectively fused, user questions are accurately matched, and the accuracy of electric power intelligent questions and answers is improved.

Description

technical field [0001] The invention belongs to the technical field of information processing, and in particular relates to a question matching method in an electric power intelligent question answering system based on a G-BI-LSTM model. Background technique [0002] With the continuous development of the Internet industry and the improvement of various service needs of power users, the traditional power customer service can no longer meet the development of business volume and user needs. The power intelligent question answering system has gradually become a popular research direction. Using new intelligent customer service technology, Realize 24 / 7 online service. How to effectively match user questions with those in the system corpus and accurately answer user questions is the core link in the process of intelligent question answering. [0003] The invention patent is a method and device for fusion of electric multi-source knowledge retrieval results, which discloses a me...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/332G06F16/35G06F40/284G06N3/04G06N3/08
CPCG06F16/3329G06F16/353G06F40/284G06N3/084G06N3/08G06N3/044G06N3/045
Inventor 胡扬波仲田许斌锋王青国陆野徐进
Owner JIANGSU ELECTRIC POWER INFORMATION TECH
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