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International Journal of Nonlinear Analysis and Applications، جلد ۱۲، شماره Special Issue، صفحات ۵۹۵-۶۰۴
عنوان فارسی
چکیده فارسی مقاله
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عنوان انگلیسی Text mining based sentiment analysis using a novel deep learning approach
چکیده انگلیسی مقاله Leveraging text mining for sentiment analysis, and integrating text mining and deep learning are the main purposes of this paper. The presented study includes three main steps. At the first step, pre-processing such as tokenization, text cleaning, stop word, stemming, and text normalization has been utilized. Secondly, feature from review and tweets using Bag of Words (BOW) method and Term Frequency $_$Inverse Document Frequency is extracted. Finally, deep learning by dense neural networks is used for classification. This research throws light on understanding the basic concepts of sentiment analysis and then showcases a model which performs deep learning for classification for a movie review and airline$_$ sentiment data set. The performance measure in terms of precision, recall, F1-measure and accuracy were calculated. Based on the results, the proposed method achieved an accuracy of $95.38%$ and $93.84%$ for a movie review and Airline$_$ sentiment, respectively.
کلیدواژه‌های انگلیسی مقاله Sentiment Analysis, Deep learning, DNN, Text mining
نویسندگان مقاله Enas Fadhil Abdullah |
Faculty of Education for Girls, University of Kufa, Al- Najaf, Iraq

Suad A. Alasadi |
College of Information Technology, University of Babylon, Babil, Iraq

Alyaa Abdulhussein Al-Joda |
Engineering Technical College of Al-Najaf,Al-Furat Al-Awsat Technical University (ATU), Al-Najaf, Iraq

نشانی اینترنتی https://ijnaa.semnan.ac.ir/article_5378_6b1a62243ff099080b64fb026193de0d.pdf
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