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An Analytical Survey on Text Classification via Deep Learning

عنوان مقاله: An Analytical Survey on Text Classification via Deep Learning
شناسه ملی مقاله: EMCE04_299
منتشر شده در چهارمین کنفرانس ملی تحقیقات کاربردی در مهندسی برق،مکانیک،کامپیوتر و فناوری اطلاعات در سال 1397
مشخصات نویسندگان مقاله:

Majid Estilayee - Technical and Engineering, Payam-e Nour, Tehran, Iran
Ali Naserasadi - Computer Group, Zarand Higher Education Complex, Kerman, Iran;

خلاصه مقاله:
Text classification is the process of assigning a text to one or more classes or categories. As one of the key issues in natural language processing, text classification recently has received a lot of attention from the researchers and different techniques have been used for this purpose. In this paper, we have investigated deep learning based text classification and defined the process while introducing and examining its different models. Finally, we have compared some of the most important models of deep learning based text classification on topic classification and sentiment analysis for two English datasets. The results show that the average accuracy of deep learning based text classification is 0.89 for sentiment analysis and is 0.83 for topic classification.

کلمات کلیدی:
Natural Language Processing, Text Classification, Machine Learning, Deep Learning

صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/870694/