Chinese-Vietnamese bilingual multi-document news viewpoint sentence recognition method based on sentence association graph

A recognition method, a technology of opinion sentences, applied in neural learning methods, character and pattern recognition, semantic analysis, etc.

Pending Publication Date: 2020-08-25
KUNMING UNIV OF SCI & TECH
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Problems solved by technology

[0004] The invention provides a Chinese-Vietnamese bilingual multi-document news opinion sentence recognition method based on the sentence association graph, which is used

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  • Chinese-Vietnamese bilingual multi-document news viewpoint sentence recognition method based on sentence association graph
  • Chinese-Vietnamese bilingual multi-document news viewpoint sentence recognition method based on sentence association graph
  • Chinese-Vietnamese bilingual multi-document news viewpoint sentence recognition method based on sentence association graph

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Embodiment 1

[0062] Example 1: Such as Figure 1-2 As shown, a Chinese-Vietnamese bilingual multi-document news opinion sentence recognition method based on sentence association graph, the specific steps are as follows:

[0063] Step 1. Use crawler tools to collect news documents from Chinese news websites and Vietnamese news websites. Manually select three topics and events that China and Vietnam are of common concern, a total of 200 documents and 2832 sentences. Each topic event is randomly divided into training set, validation set and test set according to 90%, 5%, and 5%;

[0064] Step2. Calculate the correlation strength of event elements between different sentences: first extract the named entities in Chinese-Vietnamese bilingual news sentences as event elements, and the set of Chinese event elements obtained is recorded as The set of Vietnamese event elements is recorded as In order to measure the correlation strength of the extracted elements, first use the Chinese-Vietnamese bilingu...

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Abstract

The invention relates to a Chinese-Vietnamese bilingual multi-document news viewpoint sentence recognition method based on a sentence association graph, and belongs to the technical field of natural languages. Aiming at a Chinese-Vietnamese bilingual multi-document news viewpoint sentence recognition task, the invention provides a viewpoint sentence recognition model combining sentence associationfeatures and semantic features. The method comprises the following steps: constructing a Chinese-Vietnamese bilingual multi-document association undirected graph fusing event elements and emotion elements; obtaining sentence association features of the Chinese-Vietnamese bilingual; obtaining semantic code representation of the sentence; carrying out dimensionality reduction on the obtained semantic codes to obtain sentence semantic features of the Chinese-Vietnamese bilingual; and performing joint calculation by utilizing the sentence association features and the sentence semantic features toobtain viewpoint sentence recognition features, classifying the viewpoint sentence recognition features by adopting a classifier, optimizing the classifier by adopting a binary classification cross entropy loss function, and realizing viewpoint sentence recognition by adopting the optimized classifier. The Chinese-Vietnamese bilingual multi-document news viewpoint sentence recognition method caneffectively improve the accuracy of Chinese-Vietnamese bilingual multi-document news viewpoint sentence recognition.

Description

Technical field [0001] The invention relates to a Chinese-Vietnamese bilingual multi-document news opinion sentence recognition method based on sentence association graphs, which belongs to the technical field of natural language. Background technique [0002] Carrying out Chinese-Vietnamese bilingual news opinion sentence identification research, and timely grasping of the views of China and Vietnam on the same event are essential to promote cultural exchanges and economic development between China and Vietnam. In the task of identifying opinion sentences, existing methods mainly identify opinion sentences in documents based on the characteristics of opinion sentences. For example, construct semantic features through the semantic model of opinion sentences and non-opinion sentences, then classify sentences by incorporating lexical features and part-of-speech features, and finally add high-confidence samples to the training set iteratively to obtain the final classifier. Or by c...

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Application Information

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IPC IPC(8): G06F40/211G06F40/247G06F40/30G06K9/62G06N3/04G06N3/08G06F16/9032G06F16/906G06F16/951
CPCG06F40/211G06F40/247G06F40/30G06F16/90332G06F16/906G06F16/951G06N3/049G06N3/08G06F18/2431
Inventor 余正涛唐珊王剑黄于欣高盛祥
Owner KUNMING UNIV OF SCI & TECH
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