دورية أكاديمية

Text Sentiment Analysis Based on Fusion of Attention Mechanism and BiGRU

التفاصيل البيبلوغرافية
العنوان: Text Sentiment Analysis Based on Fusion of Attention Mechanism and BiGRU
المؤلفون: YANG Qing, ZHANG Ya-wen, ZHU Li, WU Tao
المصدر: Jisuanji kexue, Vol 48, Iss 11, Pp 307-311 (2021)
بيانات النشر: Editorial office of Computer Science, 2021.
سنة النشر: 2021
المجموعة: LCC:Computer software
LCC:Technology (General)
مصطلحات موضوعية: attention mechanism, gru, glove word vector, emotion analysis, Computer software, QA76.75-76.765, Technology (General), T1-995
الوصف: Aiming at the lack of the ability of simple neural networks to capture the contextual semantics of texts and extract important information in texts,a sentiment analysis model FFA-BiAGRU is proposed,which integrates attention mechanism and GRU.First,we pre-process the text and vectorize the words through GloVe to reduce the vector space dimension.Then,through a hybrid model that fuses the attention mechanism with the update gate of the gating unit,it can extract important information in the text features.Finally,the text features are further extracted through the forced forward attention mechanism,and then classified by the softmax classifier.Experiments on public data sets show that the algorithm can effectively improve the sentiment ana-lysis performance.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: Chinese
تدمد: 1002-137X
Relation: https://www.jsjkx.com/fileup/1002-137X/PDF/1002-137X-2021-11-307.pdf; https://doaj.org/toc/1002-137X
DOI: 10.11896/jsjkx.201000075
URL الوصول: https://doaj.org/article/57227bd9aa784b19ae135d56c3138029
رقم الأكسشن: edsdoj.57227bd9aa784b19ae135d56c3138029
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:1002137X
DOI:10.11896/jsjkx.201000075