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A Chinese semantic matching system and method

A semantic matching, Chinese technology, applied in semantic analysis, neural learning methods, natural language data processing and other directions, can solve the problem of not being able to capture equivalent semantic information well

Inactive Publication Date: 2019-01-15
GUILIN UNIV OF ELECTRONIC TECH
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to provide a kind of Chinese semantics matching system and method, the technical problem to be solved is: like traditional measurement algorithm shingling and word frequency-reverse document frequency (tf-idf) algorithm etc. Good captures equivalent semantic information between question pairs

Method used

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  • A Chinese semantic matching system and method
  • A Chinese semantic matching system and method
  • A Chinese semantic matching system and method

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Embodiment 1

[0078] Such as figure 1 with figure 2 As shown, a Chinese semantic matching method includes the following steps:

[0079] S1. Collect public Quora English data sets and crawl Chinese data sets from the Internet, process the data, and convert the data into input data that can be recognized by the network;

[0080] S2. Construct a sentence pair semantic feature extraction model based on the attention mechanism and BiLSTM, process the input data using the semantic feature extraction model, and obtain the semantic features of the input data;

[0081] S3. The extracted semantic features are fused and calculated, and a predicted result is output.

[0082] In the above-mentioned embodiment, the specific implementation of S1 includes the following steps:

[0083] S1.1. Collect public Quora English data sets and crawl Chinese data sets from the Internet, and convert the data into triplet format, namely (P, Q, y); where P and Q represent two sentences, and y represents two sentences...

Embodiment 2

[0113] Such as figure 2 with image 3 As shown, a Chinese semantic matching system includes:

[0114] Preprocessing module 1 is used to collect public Quora English data sets and crawl Chinese data sets from the Internet, process the data, and convert the data into input data that can be recognized by the network;

[0115] The feature extraction module 2 is used to construct a sentence pair semantic feature extraction model based on the attention mechanism and BiLSTM, and use the semantic feature extraction model to process the input data to obtain the semantic features of the input data;

[0116] The prediction output module 3 is used to fuse and calculate the extracted semantic features, and output the prediction result.

[0117] In the foregoing embodiment, the preprocessing module 1 collects the public Quora English data set and crawls the Chinese data set from the Internet, and converts the data into a triple format, i.e. (P, Q, y); wherein P and Q represent respective...

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Abstract

The invention relates to a Chinese semantic matching system and a Chinese semantic matching method. The method comprises the following steps of: collecting a public Quora English data set and crawlingthe required Chinese data set from a network; processing the data; converting the data into input data that can be recognized by a network; a sentence pair semantic feature extraction model based onattention mechanism and BiLSTM is constructed, and the input data is processed by the semantic feature extraction model to obtain the semantic features of the input data. The extracted semantic features are fused and calculated, and the predicted results are outputted. Compared with the prior art, the invention can better capture more semantic information between two sentence pairs, thereby improving the accuracy of judging problems.

Description

technical field [0001] The invention relates to the technical field of natural language processing, in particular to a Chinese semantic matching system and method. Background technique [0002] In recent years, the community Q&A service system has become more and more popular because of its simplicity and speed. Efficiency, reducing the waiting time of questioners, and how to accurately determine whether the question has been asked before are problems that must be solved by the community question answering system. [0003] Sentence pair modeling has attracted a lot of attention in the past few years, and many tasks can be represented by matching models, such as question answering, paraphrase recognition, and semantic similarity calculation. Definition Two questions are said to be equivalent if they can be answered with the same answer. However, judging whether two questions are equivalent is a big challenge, which mainly includes two factors: (1) different people may use d...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/27G06F16/332G06F16/953G06N3/08
CPCG06N3/08G06F40/289G06F40/30
Inventor 蔡晓东侯珍珍
Owner GUILIN UNIV OF ELECTRONIC TECH
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