Opinion Mining Using LSTM Networks Ensemble for Multi-class Sentiment Analysis in E-commerce-Reference-Cited by-同舟云学术

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Opinion Mining Using LSTM Networks Ensemble for Multi-class Sentiment Analysis in E-commerce

Published:2022-12-15 Issue: Volume: Page:
ISSN:
Container-title:2022 3rd International Informatics and Software Engineering Conference (IISEC)
language:
Short-container-title:

Author:

Alnahas Dima¹,Asik Furkan²,Kanturvardar Alper¹,Ulkgun Abdullah Mert¹

Affiliation:

1. Infina Software Inc.,R&D Department,Istanbul,Turkey

2. Oneriver Software Inc.,Development Department,Istanbul,Turkey

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9998176/9998089/09998264.pdf?arnumber=9998264

Reference27 articles.

1. Türkçe metinlerde duygu analizi için farkl? makine ö?renmesi yöntemlerinin kar??la?t?r?lmas?;alpkoçak;Dokuz Eylül Üniversitesi Mühendislik Fakültesi Fenve Mühendislik Dergisi,2019

2. Sentiment Analysis Based on Deep Learning: A Comparative Study

3. Sentiment Analysis Using Word2vec And Long Short-Term Memory (LSTM) For Indonesian Hotel Reviews

4. Sentiment analysis using deep learning architectures: a review

5. Evri?imli sinir a?? mimarilerine dayal? türkçe duygu analizi;aytu?;Avrupa Bilim ve Teknoloji Dergisi,2020

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A Hybrid Hierarchical Mathematical Heuristic Solution of Sparse Algebraic Equations in Sentiment Analysis;Information;2024-08-23

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