An improved Bi-LSTM performance using Dt-WE for implicit aspect extraction-Reference-Cited by-同舟云学术

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An improved Bi-LSTM performance using Dt-WE for implicit aspect extraction

Published:2022-11-01 Issue: Volume: Page:
ISSN:
Container-title:2022 International Conference on Data Science and Intelligent Computing (ICDSIC)
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Author:

Al-Janabi Omar Mustafa¹,Ibrahim Mohammed K.¹,Kanaan-Jebna Abdulkarim²,Alyasiri Osamah Mohammed¹,Aleqabie Hiba J.³

Affiliation:

1. School of computer sciences, Universiti Sains Malaysia,Penang,Malaysia

2. Universiti Tunku Abdul Rahman,Faculty of Information and Communication Technology,Perak,Malaysia

3. Faculty of Computer Science and Information Technology,Computer Science Department,Karbala,Iraq

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10075682/10075659/10076109.pdf?arnumber=10076109

Reference36 articles.

1. Analogy-based Common-Sense Knowledge for Opinion-Target Identification and Aggregation

2. Context weight considered for implicit feature extracting

3. Aspect extraction in sentiment analysis: comparative analysis and survey

4. EXPRS: An extended pagerank method for product feature extraction from online consumer reviews

5. Using Synonym and Definition WordNet Semantic relations for implicit aspect identification in Sentiment Analysis

Cited by 2 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. Exploring aspect-based sentiment quadruple extraction with implicit aspects, opinions, and ChatGPT: a comprehensive survey;Artificial Intelligence Review;2024-01-20

2. Deep-Sentiment: An Effective Deep Sentiment Analysis Using a Decision-Based Recurrent Neural Network (D-RNN);IEEE Access;2023

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