Analysis of Performance Long Short-Term Memory-Convolutional Neural Network (LSTM-CNN) for Lifelong Learning on Indonesian Sentiment Analysis-Reference-Cited by-同舟云学术

Analysis of Performance Long Short-Term Memory-Convolutional Neural Network (LSTM-CNN) for Lifelong Learning on Indonesian Sentiment Analysis

Published:2022 Issue: Volume: Page:990-1003
ISSN:2194-5357
Container-title:Advanced Intelligent Systems for Sustainable Development (AI2SD’2020)
language:
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Author:

Suriah Gita Kartika,Hadiansah Rezki,Murfi Hendri,Ardaneswari Gianinna,Cahya Lucky Dwi,Nurhaniifah Farhatun

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-030-90639-9_80

Reference10 articles.

1. Miedema, F.: Sentiment analysis with long short-term memory networks. Vrije Universiteit Amsterdam 1, 1–17 (2018)

2. Kim, Y.: Convolutional neural networks for sentence classification. In: Proceeding of Conference on Empirical Methods in Natural Language Processing (EMNLP), pp. 1746–1751 (2014). https://doi.org/10.3115/v1/d14-1181

3. Sosa, P.M.: Twitter Sentiment Analysis Using Combined LSTM-CNN Models. Available online: https://www.academia.edu/35947062/Twitter_Sentiment_Analysis_using_combined_LSTM-CNN_Models (2017). Accessed April 2020

4. Chen, Z., Liu, B.: Lifelong Machine Learning, 2nd edn. University of Texas, Morgan & Claypool Publisher, Texas (2018). https://doi.org/10.2200/S00832ED1V01Y201802AIM037

5. Aggarwal, C.C.: Neural Networks and Deep Learning. Springer International Publishing, Cham (2018)

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