山东理工大学学报（自然科学版）2025，Vol.39Issue(5)：36-41,6.
基于BBK模型的中文文本情感分析
Chinese text sentiment analysis based on BBK model
贺国栋 1郝慧君 1王周 1王康涛 1陈伟1
作者信息
- 1. 温州商学院信息工程学院,浙江温州 325000
- 折叠
摘要
Abstract
In the field of natural language processing,sentiment analysis is a key task to understand the emotional tendency of text,but polysemy and insufficient semantic feature extraction often lead to difficul-ties in analysis.This study proposes a BERT-BiLSTM-KAN(BBK)model aimed at solving these prob-lems.First,BERT model pre-training technology is used to convert Chinese text into high-dimensional matrix vectors to fully capture the contextual information of words,phrases,and sentences.Subsequently,the bidirectional semantic features of the text are further extracted through the BiLSTM model to enhance the model's sensitivity to time series information.On this basis,the KAN model is introduced to replace traditional linear weights with learnable activation functions at the edges,which improves the model's a-bility to handle data fitting and complex feature representation.Experimental results show that the BBK model has significantly improved precision,recall and F1 score,verifying its effectiveness and superiority in Chinese text sentiment analysis.关键词
情感分析/自然语言处理/BERT模型/BiLSTM模型/KAN模型Key words
sentiment analysis/natural language processing/BERT model/BiLSTM model/KAN model分类
信息技术与安全科学引用本文复制引用
贺国栋,郝慧君,王周,王康涛,陈伟..基于BBK模型的中文文本情感分析[J].山东理工大学学报（自然科学版）,2025,39(5):36-41,6.
