Implementation of Financial Audited Robot Question and Answer Technology of Feature Processing and Improved Bi-LSTM

Liu, Bingru; Zhao, Qing

doi:10.1155/2022/7213395

Cited by 1 publication

(1 citation statement)

References 24 publications

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“…Online public opinion information generally appears on online social platforms in the form of text, and the essence of sentiment analysis of online public opinion is refected in the study of public opinion texts [17][18][19]. Te text sentiment classifcation task usually consists of two parts: text vectorized representation and sentiment classifcation.…”

Section: Bcbl Sentiment Classification Modelmentioning

confidence: 99%

Network Public Opinion Risk Prediction and Judgment Based on Deep Learning: A Model of Text Sentiment Analysis

Yang

2022

Computational Intelligence and Neuroscience

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Under the background of the gradual development and popularization of mobile Internet information technology, this paper realizes network public opinion monitoring and emotion analysis based on the deep learning method, aiming at the research needs of people’s ideological changes and emotional trends. Aiming at the shortcomings of sentiment dictionaries or machine learning methods in sentiment analysis tasks, this paper builds a sentiment classification model based on deep learning methods. First, the current main text preprocessing methods are introduced, and then a sentiment classification model, BCBL, is proposed, combining BERT, CNN, and Bi LSTM. Compared with traditional models, BCBL can better complete text sentiment classification tasks on standard datasets. Next, in view of the problem that BCBL does not consider the distribution of vocabulary weights, an attention mechanism is introduced to improve BCBL, and then the BCBL-Att model is proposed. Set up multiple sets of comparative experiments again and find that the classification effect and overall performance of BCBL-Att on standard datasets are better than BCBL, indicating that BCBL-Att has more advantages in text sentiment classification tasks.

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Section: Bcbl Sentiment Classification Modelmentioning

confidence: 99%

Network Public Opinion Risk Prediction and Judgment Based on Deep Learning: A Model of Text Sentiment Analysis

Yang

2022

Computational Intelligence and Neuroscience

View full text Add to dashboard Cite

show abstract

Implementation of Financial Audited Robot Question and Answer Technology of Feature Processing and Improved Bi-LSTM

Cited by 1 publication

References 24 publications

Network Public Opinion Risk Prediction and Judgment Based on Deep Learning: A Model of Text Sentiment Analysis

Network Public Opinion Risk Prediction and Judgment Based on Deep Learning: A Model of Text Sentiment Analysis

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