Text Fine-grained Sentiment Generation Method Based on Probabilistic Reasoning and Sentiment Cognition

A probabilistic reasoning, fine-grained technology, applied in electrical digital data processing, natural language data processing, instruments, etc., can solve problems such as ignoring implicit emotions

Active Publication Date: 2021-09-21
福昕鲲鹏(北京)信息科技有限公司
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Problems solved by technology

[0004] Aiming at the defects of the prior art, the present invention proposes a text fine-grained emotion generation method based on probabilistic reasoning and emotion cognition, using the emotion cognition method to solve the problem of ignoring implicit emotions in other emotion generation methods, and using Bayeux The Si network calculates the probability of emotion generation and improves the accuracy of emotion category generation

Method used

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  • Text Fine-grained Sentiment Generation Method Based on Probabilistic Reasoning and Sentiment Cognition
  • Text Fine-grained Sentiment Generation Method Based on Probabilistic Reasoning and Sentiment Cognition
  • Text Fine-grained Sentiment Generation Method Based on Probabilistic Reasoning and Sentiment Cognition

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Embodiment 1

[0103] Text: / / @微博 Funny Ranking: Gulangyu is really good, let's go on a trip together! [rejoice]

[0104] 1) Prepare the text data set S required for the training method with a total of 15,000 items, and mark the text according to seven emotions: like, happiness, fear, anger, disgust, sadness, and surprise.

[0105] 2) The text data set S is analyzed, part-of-speech tagging, dependency syntactic analysis, semantic dependency and other processing using the language cloud technology platform of Harbin Institute of Technology.

[0106] 3) Use the emotional evaluation variables extracted in step 3 above to construct the Bayesian network.

[0107] 4) According to the characteristics of the network text, determine the emotional evaluation variables based on emoticons , where exp indicates whether there are emoticons, and other variables indicate the corresponding emotional types. 1, yes 2; determined based on the statistical word frequency emotional evaluation variables indicate...

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Abstract

The present invention relates to a text fine-grained emotion generation method based on probabilistic reasoning and emotional cognition, comprising the following steps: Step 1: Prepare the text data set required by the training method; Step 2: Process the text data set; Step 3: Extract and construct Sentiment evaluation variables used by the Bayesian network; Step 4: According to the characteristics of the network text, add emotional evaluation variables based on emoji and word frequency; Step 5: Build an emotional knowledge base; Step 6: Build a common sense knowledge base; Step 7: Emotion Evaluation variable assignment; Step 8: Learning the network structure of the Bayesian network for emotion generation; Step 9, parameter learning; Step 10: Complete the construction of the emotion generation method. The present invention uses the emotion recognition method to solve the problem of ignoring the hidden emotion existing in other emotion generation methods, and uses the Bayesian network to calculate the probability of emotion generation, compares the probability of each emotion category, and generates one or more emotion.

Description

technical field [0001] The present invention relates to the field of machine learning and natural language processing text sentiment analysis, in particular to the field of emotion cognition methods and Bayesian network reasoning ideas, and in particular to a text fine-grained emotion generation method based on probabilistic reasoning and emotion cognition. Background technique [0002] Text sentiment analysis is a popular research field in natural language processing, mainly to automatically identify the emotional categories expressed by users in text. Emotion is a psychological and physiological state produced by a variety of feelings, thoughts, and behaviors. It generally refers to likes, dislikes, anger, surprise, pride, etc. Traditional sentiment analysis is mainly to identify the user's emotional tendency: positive, negative or neutral, while sentiment analysis is a fine-grained sentiment analysis task that can identify multiple emotions. The methods of emotion genera...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F40/205G06F40/247
CPCG06F40/205G06F40/247
Inventor 柴玉梅徐源音王黎明张卓韩飞韩慧李永帅
Owner 福昕鲲鹏(北京)信息科技有限公司
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