این سایت در حال حاضر پشتیبانی نمی شود و امکان دارد داده های نشریات بروز نباشند
International Journal of Information and Communication Technology Research (IJICT، جلد ۱۱، شماره ۳، صفحات ۵۷-۶۷
عنوان فارسی
چکیده فارسی مقاله
کلیدواژه‌های فارسی مقاله
عنوان انگلیسی mproving the Performance of Text Sentiment Analysis using Deep Convolutional Neural Network Integrated with Hierarchical Attention Layer
چکیده انگلیسی مقاله Sentiment analysis is considered as one of the most essential tasks in the field of natural language processing and cognitive science. In order to enhance the performance of sentiment analysis techniques, it is necessary to not only classify the sentences based on their sentimental labels but also to extract the informative words that contribute to the classification decision. In this regard, deep neural networks based on the attention mechanism have achieved considerable progress in recent years. However, there is still a limited number of studies on attention mechanisms for text classification and especially sentiment analysis. To fill this lacuna, a Convolution Neural Network (CNN) integrated with attention layer is presented in this paper that is able to extract informative words and assign them higher weights based on the context. In the attention layer, the proposed model employs a context vector and tries to measure the importance of a word as the similarity between the context vector and word vector. Then, by integrating the new vectors obtained from the attention layer into sentence vectors, the new generated vectors are used for classification. In order to verify the performance of the proposed model, various experiments were conducted on the Stanford datasets. Based on the results of the experiments, the proposed model not only significantly outperforms other existing studies but also is able to consider the context to extract the informative words which can be considered as a value in analysis and application.
کلیدواژه‌های انگلیسی مقاله Natural language processing, Sentiment analysis, Deep Learning, Convolutional neural network, Attention mechanism
نویسندگان مقاله | Hossein Sadr
Department of Computer Engineering, Rasht Branch, Islamic Azad University, Rasht, Iran


| Mir Mohsen Pedram
Department of Electrical and Computer Engineering, Faculty of Engineering, Kharazmi University ,Tehran, Iran


| Mohammad Teshnelab
Industrial Control Center of Excellence, Faculty of Electrical and Computer Engineering, K. N. Toosi University, Tehran, Iran
نشانی اینترنتی http://ijict.itrc.ac.ir/browse.php?a_code=A-10-581-1&slc_lang=en&sid=1
فایل مقاله فایلی برای مقاله ذخیره نشده است
کد مقاله (doi)
زبان مقاله منتشر شده en
موضوعات مقاله منتشر شده فناوری اطلاعات
نوع مقاله منتشر شده پژوهشی
برگشت به: صفحه اول پایگاه   |   نسخه مرتبط   |   نشریه مرتبط   |   فهرست نشریات