Text perception based emotion feedback method and apparatus, computer device and storage medium

Abstract

The present application relates to a text perception based emotion feedback method and apparatus, a computer device and a storage medium. The method comprises: calculating obtained to-be-fed back textcontent by using a text content perceptor to obtain the first weight distribution ratio and the second weight distribution ratio; inputting the to-be-fed back text content into a trained neural network to obtain an emotion classification result; calculating emotion words in the to-be-fed back text content according to a preset rule in a preset dictionary to obtain a corresponding emotion index result; according to the first weight distribution ratio and the second weight distribution ratio, weighting the emotion classification result and the emotion index result to obtain an emotion analysisresult; obtaining an emotional opinion result corresponding to the to-be-fed back text content; and according to the emotion analysis result and the emotional opinion result, selecting a target emotional feedback comment reply corresponding to the to-be-fed back text content from a preset comment reply association library. By virtue of the technical scheme of the present application, the matchingrate between the to-be-fed back text content and the target emotional feedback reply can be improved.

Description

technical field [0001] The present application relates to the field of computer technology, in particular to a method, device, computer equipment and storage medium for emotional feedback based on text perception. Background technique [0002] Emotional interaction generally refers to the analysis of content sources such as documents to determine the specific response or attitude conveyed by the content source, and then perform intelligent and interesting emotional feedback on the basis of emotional analysis and contact. For example, if you feel dissatisfied with online shopping on the Taobao client, and then give a bad review, the computer will automatically give an interesting and emotional reply based on the sentiment analysis results. Dear, what you said does exist. We are constantly Improve this appearance, please live happily every day! [0003] At present, the mainstream commonly used text sentiment analysis is based on neural network feature classification or sentim...

AI Technical Summary

Problems solved by technology

[0003] At present, the mainstream commonly used text sentiment analysis is based on neural network feature classification or sentiment score calculation based on emotional lexicon. However, although neural network feature classification has great advantages and accuracy in discriminating emotional text content at the paragraph level, but It is impossible to score specific passages and extract emotional words. Although the algorithm based on the sentiment dictionary can accurately extract emotional words and have emotional classification, the training effect on long texts of chapters and paragraphs is not good.

Therefore, the emotional feedback of emotional text content at the paragraph level cannot be recognized by traditional technology based on neural network feature classification or emotion dictionary-based algorithms, and the recognition matching rate is low and the effect is not good.

Images