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Multi-Attention Fusion Modeling for Sentiment Analysis of Educational Big Data 被引量:5
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作者 guanlin zhai Yan Yang +1 位作者 Heng Wang Shengdong Du 《Big Data Mining and Analytics》 EI 2020年第4期311-319,共9页
As an important branch of natural language processing,sentiment analysis has received increasing attention.In teaching evaluation,sentiment analysis can help educators discover the true feelings of students about the ... As an important branch of natural language processing,sentiment analysis has received increasing attention.In teaching evaluation,sentiment analysis can help educators discover the true feelings of students about the course in a timely manner and adjust the teaching plan accurately and timely to improve the quality of education and teaching.Aiming at the inefficiency and heavy workload of college curriculum evaluation methods,a Multi-Attention Fusion Modeling(Multi-AFM)is proposed,which integrates global attention and local attention through gating unit control to generate a reasonable contextual representation and achieve improved classification results.Experimental results show that the Multi-AFM model performs better than the existing methods in the application of education and other fields. 展开更多
关键词 educational big data sentiment analysis aspect-level ATTENTION
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