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A Cross-Domain Sentiment Analysis Method Based on Sentiment Polarity Enhanced Semantics

A technology of emotional polarity and sentiment analysis, applied in the field of text analysis, to achieve the effect of narrowing the differences between fields

Active Publication Date: 2021-10-15
YUNNAN UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, even though these methods consider the bridge function of shared words between domains, they only use single and simple metrics such as co-occurrence and word frequency to select shared words.

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  • A Cross-Domain Sentiment Analysis Method Based on Sentiment Polarity Enhanced Semantics
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  • A Cross-Domain Sentiment Analysis Method Based on Sentiment Polarity Enhanced Semantics

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Embodiment

[0027] figure 1 The method flowchart provided for the embodiment of the present invention, such as figure 1 As shown, the method may include the following steps:

[0028] Step 101: Extract terms and vectorize:

[0029] In the implementation of the present invention, for example, English text can extract unigram and bigrams words as source domain terms through word segmentation, part-of-speech restoration, and removal of stop words W S and target domain terms W T ; Based on word2vec, the term W S and W T Vectorized, denoted as , .

[0030] Step 102: extracting a shared word set;

[0031] First, statistics W S ∩ W T The word frequency of each word in the source domain and the target domain; the selected word frequency is greater than the preset threshold β words, of which β is a positive integer ，β It can be preferred that 2≤β≤10;

[0032] Secondly, in the implementation of the present invention, according to the HowNet polar dictionary, N positive words an...

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Abstract

The invention belongs to the field of text analysis and discloses a cross-domain emotion analysis method based on emotion polarity enhanced semantics. The present invention extracts the lexical items of the source field and the target field emotional text, and vectorizes; secondly, selects the lexical items with strong emotion and consistent semantics between the source field and the target field as the shared words between the fields; thirdly, based on the shared word Emotional polarity expands the emotional text respectively, and retrains the word vector to enhance the emotional semantics; finally, based on the convolutional neural network, the emotional features of the text are automatically extracted, and a classifier is trained to complete the classification of the emotional text in the target field. The invention considers the emotional polarity of shared words and the consistency of emotional semantics between domains, as well as the influence on the extraction and classification of emotional features, and is more in line with the actual characteristics and requirements of cross-domain emotional analysis.

Description

technical field [0001] The invention belongs to the field of text analysis, relates to a cross-domain sentiment analysis method, and more specifically relates to a selection of shared words in an emotional text and a method for enhancing emotional semantics based on the shared words. Background technique [0002] Emotional texts refer to texts with subjective emotional tendencies. The analysis of the emotional tendency of the text is an important technical basis for applications such as public opinion monitoring, word-of-mouth analysis, and topic monitoring. Cross-domain sentiment analysis studies the technical issue of how to make full use of relevant source domain samples for analysis under the condition that sentiment has topic correlation and domain correlation, and the samples in the target domain are sparse. [0003] The key to solving cross-domain sentimental text analysis is to narrow the difference between the source domain and the target domain, transfer the knowl...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F16/35G06F40/216
CPCG06F16/35G06F40/216
Inventor 姬晨李维华王翔郭延哺段云浩
Owner YUNNAN UNIV