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Semantic feature cube-based sentence pair semantic matching method for intelligent questions and answers

A semantic feature and semantic matching technology, applied in semantic analysis, natural language data processing, special data processing applications, etc., can solve the problem of not fully exploiting and utilizing the timing information of sentences

Active Publication Date: 2020-11-27
QILU UNIV OF TECH
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  • Description
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  • Application Information

AI Technical Summary

Problems solved by technology

In summary, one-dimensional convolutional neural network, two-dimensional convolutional neural network and recurrent neural network have failed to fully exploit the timing information in sentences.

Method used

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  • Semantic feature cube-based sentence pair semantic matching method for intelligent questions and answers
  • Semantic feature cube-based sentence pair semantic matching method for intelligent questions and answers
  • Semantic feature cube-based sentence pair semantic matching method for intelligent questions and answers

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Embodiment 1

[0115] as attached Figure 8 As shown, the main framework structure of the present invention includes a multi-granularity embedding module, a deep semantic feature cube construction network module, a feature transformation network module and a label prediction module. Among them, the multi-granularity embedding module performs embedding operations on the input sentence at word granularity and word granularity, and passes the result to the deep semantic feature cube construction network module of the model. The deep semantic feature cube construction network module contains several layers of encoding structures, such as Figure 7 As shown, the first-layer encoding structure encodes the word embedding representation and the word embedding representation output by the multi-granularity embedding module respectively to obtain the first-layer word encoding result and the first-layer word encoding result; the first-level word encoding result and the first-level word encoding result...

Embodiment 2

[0121] as attached figure 1 As shown, the present invention is oriented to intelligent question answering based on the semantic feature cube sentence-to-semantic matching method, and the specific steps are as follows:

[0122] S1. Construct a sentence pair semantic matching knowledge base, as attached figure 2 As shown, the specific steps are as follows:

[0123] S101. Downloading datasets on the network to obtain original data: downloading datasets that have been published on the network for semantic matching of sentence pairs or artificially constructed datasets, and using them as raw data for constructing a knowledge base for semantic matching of sentence pairs.

[0124]Example: There are many public sentence-pair semantic matching data sets for intelligent question answering systems on the Internet, such as the LCQMC data set [Xin Liu, Qingcai Chen, Chong Deng, Huajun Zeng, Jing Chen, Dongfang Li, and Buzhou Tang.Lcqmc:A large-scale chinese question matching corpus, COL...

Embodiment 3

[0249] as attached Image 6 As shown, based on the sentence-to-semantic matching device based on the intelligent question answering based on the semantic feature cube of embodiment 2, the device includes,

[0250] The sentence-pair semantic matching knowledge base construction unit is used to obtain a large amount of sentence-pair data, and then preprocess it to obtain a sentence-pair semantic matching knowledge base that meets the training requirements; the sentence-pair semantic matching knowledge base construction unit includes,

[0251] The sentence-pair data acquisition unit is responsible for downloading the sentence-pair semantic matching datasets that have been published on the network or artificially constructed datasets, and using them as the original data for constructing the sentence-pair semantic matching knowledge base;

[0252] The original data hyphenation preprocessing or word segmentation preprocessing unit is responsible for preprocessing the raw data used t...

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Abstract

The invention discloses a semantic feature cube-based sentence pair semantic matching method for intelligent questions and answers, and belongs to the technical field of artificial intelligence and natural language processing. The technical problem to be solved by the invention is how to capture more semantic context features, time sequence features, the relationship of coded information between different dimensions and interaction information between sentences, and intelligent semantic matching of sentence pairs is realized. The adopted technical scheme is as follows: a sentence pair semanticmatching model consisting of a multi-granularity embedding module, a deep semantic feature cube construction network module, a feature conversion network module and a label prediction module is constructed and trained; and deep semantic feature cube representation of sentence information and three-dimensional convolutional encoding representation of semantic features are realized, and meanwhile,a final matching tensor of sentence pairs is generated through an attention mechanism, and the matching degree of the sentence pairs is judged, so that the purpose of intelligent semantic matching ofthe sentence pairs is achieved. The device comprises a sentence pair semantic matching knowledge base construction unit, a training data set generation unit, a sentence pair semantic matching model construction unit and a sentence pair semantic matching model training unit.

Description

technical field [0001] The invention relates to the technical fields of artificial intelligence and natural language processing, in particular to a sentence pair semantic matching method based on semantic feature cubes for intelligent question answering. Background technique [0002] The intelligent question answering system is one of the core technologies of human-computer interaction. It can automatically find matching standard questions in the question and answer knowledge base for the questions raised by users, and push the answers to the standard questions to users, which can greatly reduce the burden of manual answers. . Intelligent question answering system has a wide range of practical applications in self-service, intelligent customer service and other fields. For the vastly different questions raised by users, how to find matching standard questions for them is the core technology of the intelligent question answering system. The essence of this technology is to ...

Claims

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Application Information

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IPC IPC(8): G06F16/33G06F16/332G06F40/289G06F40/30G06K9/62G06N3/04
CPCG06F16/3344G06F16/3329G06F40/30G06F40/289G06N3/045G06F18/214
Inventor 鹿文鹏于瑞张旭
Owner QILU UNIV OF TECH
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