Towards Mining Public Opinion: An Attention-Based Long Short Term Memory Network Using Transfer Learning

Hossain, G. M. Sakhawat and Rashid, Md. Harun Or and Islam, Md. Rafiqul and Sarker, Ananya and Yasmin, Must. Asma (2022) Towards Mining Public Opinion: An Attention-Based Long Short Term Memory Network Using Transfer Learning. Journal of Computer and Communications, 10 (06). pp. 112-131. ISSN 2327-5219

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Abstract

The Internet provides a large number of tools and resources, such as social media sites, online newsgroups, blogs, electronic forums, virtual communities, and online travel sites, for consumers to express their views or opinions regarding various issues. These opinions can help organizations like tourism to improve their products and services for their consumers. Opinion mining refers to a process of identifying emotions by applying Natural Language Processing (NLP) techniques to a pool of texts. This paper mainly focuses on mining public opinion from the hotel reviews domain. To do so, we proposed a novel technique called the Attention-Based Long Short Term Memory (Attention-LSTM) Network using a transfer learning approach. We empirically analyzed several machine learning and deep learning methods and observed our proposed technique provided an adequate performance for mining public opinion in the hotel reviews domain.

Item Type: Article
Subjects: STM Article > Computer Science
Depositing User: Unnamed user with email support@stmarticle.org
Date Deposited: 05 May 2023 09:47
Last Modified: 19 Jun 2024 11:52
URI: http://publish.journalgazett.co.in/id/eprint/1139

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