A method and device for sentiment analysis and noise reduction of e-commerce reviews

A sentiment analysis and noise reduction technology, applied in the field of sentiment analysis noise reduction of e-commerce reviews, can solve problems such as inability to guarantee accuracy, wrong decision-making direction, errors, etc., and achieve the effect of accurate sentiment analysis results, improved products, and reasonable review results

Active Publication Date: 2022-06-24
上海宝尊电子商务有限公司
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Problems solved by technology

The problem encountered by this solution is that once the user makes malicious comments, floods, repeatedly emphasizes, and exaggerates the problem, the result will be enlarged or the wrong result will be obtained. The accuracy rate cannot be guaranteed, and it cannot help the merchant to effectively identify. get wrong decision direction
And about the method and the device of this business comment emotion analysis noise reduction, there is no report yet

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  • A method and device for sentiment analysis and noise reduction of e-commerce reviews
  • A method and device for sentiment analysis and noise reduction of e-commerce reviews
  • A method and device for sentiment analysis and noise reduction of e-commerce reviews

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Embodiment Construction

[0067] The specific embodiments provided by the present invention will be described in detail below with reference to the accompanying drawings.

[0068] Please refer to figure 1 , figure 1 It is a schematic flowchart of a method for denoising the sentiment analysis of e-commerce reviews of the present invention. A method for denoising sentiment analysis of e-commerce reviews, the method comprises the following steps:

[0069] S1. Construction of pre-marking module:

[0070] S11. Create an emotional thesaurus tag, match emotional words to emotional tags, add [invalid tag] corresponding vocabulary copy, paste, naughty value, etc., and export the tags to text.

[0071] S12. Read the Tmall comment data in batches, segment the comment data sentence by sentence, match the word segmentation results according to the keywords of the emotional thesaurus, and perform machine labeling on the matched results according to tags. A comment can have multiple tags, generating text by line....

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Abstract

The present invention relates to a method and device for sentiment analysis and noise reduction of e-commerce reviews. The method includes the following steps: step S1, construction of a pre-marking module; step S2, construction of a manual tagging module: Step S3, construction of the deep neural network model training module: step S4, construction of the deep neural network model labeling module: step S5, construction of the noise reduction module: step S6, construction of the sentiment analysis module. Its advantages are as follows: it can help merchants find and correct malicious comments, flood, repeatedly emphasize, and exaggerate comments, eliminate or reduce the impact of these noises, and make sentiment analysis results more accurate.

Description

technical field [0001] The invention relates to the technical field of natural language processing, and in particular, relates to a method and a device for denoising the sentiment analysis of e-commerce reviews. Background technique [0002] Sentiment analysis is to classify texts into two or more types of positive or negative meanings based on the meaning and emotional information expressed by the text. The purpose is to find out the speaker's attitude on some topic or against a bipolar view of a text, which expresses the speaker's emotional state. In the field of e-commerce, the comments of users after purchasing a product directly express their emotional attitude towards the product, which is of great help to help merchants improve products and improve user satisfaction. [0003] At present, there are many solutions for sentiment analysis, which mainly use sentiment words, negative words, degree adverbs, and domain dictionaries to build models, and generate feature vecto...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F16/35G06F16/36G06F40/289G06F40/247G06F40/242G06Q30/02
CPCG06Q30/0282G06F40/242G06F40/247G06F40/289
Inventor 李平章王航
Owner 上海宝尊电子商务有限公司
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