TY - GEN
T1 - Analysis of Convolutional Neural Network for Lifelong Learning on Indonesian Sentiment Analysis
AU - Abdurrahman, Zaid
AU - Murfi, Hendri
AU - Widyaningsih, Yekti
N1 - Publisher Copyright:
© 2020 ACM.
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2020/1/14
Y1 - 2020/1/14
N2 - Sentiment analysis is a process to obtain the tendency of the authors in an article. Sentiment analysis classifies textual data into a class of positive, negative, or neutral sentiments. CNN is one of the deep learning algorithms capable of classifying textual data into positive, negative, or natural classes. In general, the standard learning methods learn from one domain to produce a model. Another learning paradigm is lifelong learning which is believed to be able to accumulate learning from various domains for learning in the new domain. In this paper, we examine lifelong learning of CNN for sentiment analysis on Indonesian textual data. Our simulation shows that the accuracy of CNN increases with the increase in the number of source domains where CNN learns. This shows that lifelong learning using CNN works well for sentiment analysis on Indonesian textual data.
AB - Sentiment analysis is a process to obtain the tendency of the authors in an article. Sentiment analysis classifies textual data into a class of positive, negative, or neutral sentiments. CNN is one of the deep learning algorithms capable of classifying textual data into positive, negative, or natural classes. In general, the standard learning methods learn from one domain to produce a model. Another learning paradigm is lifelong learning which is believed to be able to accumulate learning from various domains for learning in the new domain. In this paper, we examine lifelong learning of CNN for sentiment analysis on Indonesian textual data. Our simulation shows that the accuracy of CNN increases with the increase in the number of source domains where CNN learns. This shows that lifelong learning using CNN works well for sentiment analysis on Indonesian textual data.
KW - Convolutional Neural Network
KW - Lifelong Learning
KW - Machine Learning
KW - Sentiment Analysis
UR - http://www.scopus.com/inward/record.url?scp=85096308494&partnerID=8YFLogxK
U2 - 10.1145/3424311.3424331
DO - 10.1145/3424311.3424331
M3 - Conference contribution
AN - SCOPUS:85096308494
T3 - ACM International Conference Proceeding Series
SP - 64
EP - 69
BT - ICICSE and ICACTE 2020 - Proceedings of 2020 International Conference on Internet Computing for Science and Engineering - 2020 the 13th International Conference on Advanced Computer Theory and Engineering
PB - Association for Computing Machinery
T2 - 2020 International Conference on Internet Computing for Science and Engineering, ICICSE 2020 and the 13th International Conference on Advanced Computer Theory and Engineering, ICACTE 2020
Y2 - 18 September 2020 through 20 September 2020
ER -