Improving the Extraction of Aspect Terms from Customer Reviews using MSRL-NET and BERT-Reference-Cited by-同舟云学术

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Improving the Extraction of Aspect Terms from Customer Reviews using MSRL-NET and BERT

Published:2024-03-22 Issue: Volume:21 Page:1-7
ISSN:
Container-title:2024 International Conference on Trends in Quantum Computing and Emerging Business Technologies
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Author:

Gupta Shivani¹,K Rakhesh²,Velmurugan S³,Brindha T V⁴

Affiliation:

1. Pranveer Singh Institute of Technology,Department of Computer Science and Engineering,Kanpur,India

2. Shri Jagdishprasad Jhabarmal Tibrewala University,Department of Computer Science and Engineering,Rajasthan,India

3. RMD Engineering College, Kavarapettai,Department of Information and Technology,Chennai,India

4. Sri Venkateshwara College of Engineering,Department of Computer Science and Engineering,Tiruvallur,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10543254/10545024/10545177.pdf?arnumber=10545177

Reference15 articles.

1. An unsupervised aspect extraction strategy for monitoring real-time reviews stream

2. Implicit aspect extraction in sentiment analysis: Review, taxonomy, oppportunities, and open challenges

3. Multi-level knowledge-based approach for implicit aspect identification

4. Enhancing Aspect-Based Sentiment Analysis of Arabic Hotels’ reviews using morphological, syntactic and semantic features

5. Attention-based long short-term memory network using sentiment lexicon embedding for aspect-level sentiment analysis in Korean

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