A BiLSTM-CF and BiGRU-based Deep Sentiment Analysis Model to Explore Customer Reviews for Effective Recommendations

IF 16.4 1区化学 Q1 CHEMISTRY, MULTIDISCIPLINARY

Accounts of Chemical Research Pub Date : 2023-10-13 DOI:10.48084/etasr.6278

Muhammad Rizwan Rashid Rana, Asif Nawaz, Tariq Ali, Ahmed M. El-Sherbeeny, Waqar Ali

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引用次数: 0

Abstract

The advancement of technology has led to the rise of social media forums and e-commerce platforms, which have become popular means of communication, and people can express their opinions through comments and reviews. Increased accessibility to online feedback helps individuals make informed decisions about product purchases, services, and other decisions. This study used a sentiment analysis-based approach to improve the functionality of the recommendations from user reviews and consider the features (aspects and opinions) of products and services to understand the characteristics and attributes that influence the performance of classification algorithms. The proposed model consists of data preprocessing, word embedding, character representation creation, feature extraction using BiLSTM-CF, and classification using BiGRU. The proposed model was evaluated on different multidomain benchmark datasets demonstrating impressive performance. The proposed model outperformed existing models, offering more promising performance results in recommendations.

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基于BiLSTM-CF和bigru的深度情感分析模型探索客户评论以获得有效推荐

科技的进步导致社交媒体论坛和电子商务平台的兴起，这些已经成为流行的交流手段，人们可以通过评论和评论来表达自己的观点。增加在线反馈的可访问性有助于个人对产品购买、服务和其他决策做出明智的决定。本研究使用基于情感分析的方法来改进来自用户评论的推荐功能，并考虑产品和服务的特征(方面和意见)，以了解影响分类算法性能的特征和属性。该模型包括数据预处理、词嵌入、字符表示创建、BiLSTM-CF特征提取和BiGRU分类。在不同的多域基准数据集上对该模型进行了评估，显示出令人印象深刻的性能。提出的模型优于现有的模型，在推荐中提供了更有希望的性能结果。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Accounts of Chemical Research 化学-化学综合

CiteScore

31.40

自引率

1.10%

发文量

312

审稿时长

2 months

期刊介绍： Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.