Comment word emotion analysis method and system based on deep learning

A sentiment analysis and deep learning technology, applied in semantic analysis, special data processing applications, instruments, etc., can solve the problems of weakening the expression tendency information of emotional words and low accuracy, and achieve the effect of improving accuracy and enhancing information strength.

Inactive Publication Date: 2017-10-24
DATAGRAND TECH INC
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Problems solved by technology

However, there are also disadvantages in not using an emotional dictionary, which is equivalent to weakening the tendency information expressed by

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  • Comment word emotion analysis method and system based on deep learning
  • Comment word emotion analysis method and system based on deep learning
  • Comment word emotion analysis method and system based on deep learning

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Embodiment Construction

[0043] In order to enable those skilled in the art to better understand the technical solutions of the present invention, the present invention will be further described in detail below in conjunction with the accompanying drawings.

[0044] Such as figure 1 As shown, the present invention provides a kind of review word emotion analysis method based on deep learning, comprises the following steps:

[0045] S101. Receive the text to be commented, segment the text to be commented, and obtain a sequence of words;

[0046] Internet users start to develop from simply "reading" webpages to "writing" webpages and "co-constructing" the Internet, and move forward from passively receiving Internet information to actively creating Internet information. Therefore, a large amount of user-participated, valuable commentary information (such as movie reviews, shopping experience, etc.) such as characters, events, products, etc., has been generated on the Internet, specifically on blogs, foru...

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Abstract

The invention discloses a comment word emotion analysis method and system based on deep learning. The method includes the steps: receiving a text to be commented, and segmenting the text to be commented to obtain a word sequence; transforming the word sequence into a corresponding word vector sequence by a word vector generation model; judging whether the word sequence comprises emotion tendency words or not according to a domain emotion dictionary, acquiring a corresponding expansion word vector according to the emotion tendency words and adding the expansion word vector into the word vector sequence; inputting the word vector sequence with the added expansion word vector into an emotion judgment model and outputting judgment results. A traditional word vector is expanded based on the domain emotion dictionary, the information intensity of domain emotion words is enhanced, emotion tendency of the domain emotion words in a specific domain can be accurately recognized, and emotion tendency analysis accuracy is effectively improved.

Description

technical field [0001] The invention relates to the technical fields of sentiment analysis and natural language processing, in particular to a method and system for sentiment analysis of comment words based on deep learning. Background technique [0002] Today, with the increasingly developed Internet, many users will go to the official website of the brand or some professional websites and social media to post product evaluations after purchasing products through e-commerce websites or offline stores, including buying cars and mobile phones. For buyers, reviews are an important way to understand the real situation of a product. For merchants, reviews are the first-hand channel to learn about customer feedback, product benefits, and potential issues. Therefore, there is a considerable market demand for mining and analyzing comment data. Judging the sentimental orientation of comments, that is, whether a comment text expresses positive or negative sentiments, is the core of...

Claims

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Application Information

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IPC IPC(8): G06F17/27
CPCG06F40/242G06F40/289G06F40/30
Inventor 纪传俊陈运文纪达麒桂洪冠江永青
Owner DATAGRAND TECH INC
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