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Text sentiment analysis method and system, and computer readable storage medium

A sentiment analysis and text technology, applied in computing, special data processing applications, instruments, etc., can solve the problems of high labor cost and neglect, and achieve the effect of improving accuracy and strong generalization ability

Inactive Publication Date: 2018-06-15
CENT SOUTH UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Although the above method has the advantages of strong scalability, but the labor cost is high, and the context semantic information is ignored

Method used

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  • Text sentiment analysis method and system, and computer readable storage medium
  • Text sentiment analysis method and system, and computer readable storage medium
  • Text sentiment analysis method and system, and computer readable storage medium

Examples

Experimental program
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Embodiment 1

[0035] This embodiment discloses a text sentiment analysis method.

[0036] The method of this embodiment includes:

[0037] Step S1: Perform word segmentation on the original text, obtain a text word set, and train the obtained text word set to generate a word vector matrix.

[0038] Optionally, in this step, jieba is used for word segmentation, and word2vec is used for training to generate a word vector matrix.

[0039] Step S2, splitting the word vector matrix in units of sentences, inputting the word vector corresponding to any sentence into the preset LSTM network model, and obtaining the hidden layer vector of each word; When the word vector is input to the preset LSTM network model, a word corresponds to a hidden layer unit, and the hidden information between the sentence contexts is extracted through the correlation between the adjacent hidden layers of the LSTM, and the last word of the sentence corresponds to the hidden information. The hidden layer vector is used ...

Embodiment 2

[0058] This embodiment discloses a text sentiment analysis system, including a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor implements the steps of the above method embodiments when the processor executes the computer program.

Embodiment 3

[0060] This embodiment discloses a computer-readable storage medium on which a computer program is stored, and when the program is executed by a processor, implements the steps of the foregoing method embodiments.

[0061] To sum up, the text sentiment analysis method, system and computer-readable storage medium disclosed by the above-mentioned embodiments of the present invention perform text sentiment analysis based on LSTM and attention model, and have the following beneficial effects:

[0062] Since sentiment analysis belongs to the field of natural language processing, its core task is to extract the emotional information features of the input text to provide the basis for the final classification. The invention takes the better sentence vector representation as the starting point, grasps the source of sentiment analysis, uses the attention mechanism and the LSTM model to process and predict the input text, associates the input and output, and considers the sentence struct...

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Abstract

The invention relates to the technical field of artificial intelligence, and discloses a text sentiment analysis method, a text sentiment analysis system and a computer readable storage medium, for improving the accuracy of text sentiment analysis. The method comprises the steps of inputting a word vector corresponding to any sentence into a preset LSTM network model, thus acquiring a hiding layervector of each word; tagging the part-of-speech of an acquired text word set, training the text word set carrying part-of-speech tagging information, and splitting a part-of-speech vector matrix generated by training by using words as units, thus acquiring the part-of-speech vector corresponding to each word; using sentences as units, performing word embedding weighted summation attention analysis on the hiding layer vector and the part-of-speech vector corresponding to each word in the sentence to acquire a sentence vector carrying attention information of each sentence, and using the sentence vector carrying the attention information to serve as the input of a sentiment classification model, thus acquiring a sentiment classification result of each sentence and / or a classification resultof the original text.

Description

technical field [0001] The present invention relates to the technical field of artificial intelligence, and in particular, to a text sentiment analysis method, system and computer-readable storage medium. Background technique [0002] With the rise of social media such as Weibo and Twitter, people not only obtain information from the Internet, but also fully express their opinions and share their experiences through social media. For example: commenting on hot events, describing views on movies, describing views on a song, describing product experience, etc., resulting in a large number of texts with subjective emotional information. The government fully grasps the ideological dynamics of the public and provides the basis for correct public opinion guidance. It can also mine the user's preference for the product, help merchants understand the product advantages and potential problems, so as to provide users with a better product experience. At the same time, it can also he...

Claims

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Application Information

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IPC IPC(8): G06F17/27G06N3/04
CPCG06N3/049G06F40/205G06F40/279
Inventor 王斌唐玲艳刘家广严毅康王淼盛津芳
Owner CENT SOUTH UNIV
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