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Wando Mount Pleasant Library
9 a.m. - 8 p.m.
Phone: (843) 805-6888
Main Library
9 a.m. - 8 p.m.
Phone: (843) 805-6930
McClellanville Library
9 a.m. - 6 p.m.
Phone: (843) 887-3699
Folly Beach Library
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Phone: (843) 588-2001
Miss Jane's Building (Edisto Library Temporary Location)
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West Ashley Library
9 a.m. - 7 p.m.
Phone: (843) 766-6635
John L. Dart Library
9 a.m. - 7 p.m.
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St. Paul's/Hollywood Library
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Mt. Pleasant Library
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Dorchester Road Library
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Edgar Allan Poe/Sullivan's Island Library
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John's Island Library
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A BiLSTM-CF and BiGRU-based Deep Sentiment Analysis Model to Explore Customer Reviews for Effective Recommendations.
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- Author(s): Rana, Muhammad Rizwan Rashid; Nawaz, Asif; Ali, Tariq; El-Sherbeeny, Ahmed M.; Ali, Waqar
- Source:
Engineering, Technology & Applied Science Research; Oct2023, Vol. 13 Issue 5, p11739-11746, 8p- Subject Terms:
- Source:
- Additional Information
- 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 analysisbased 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. [ABSTRACT FROM AUTHOR]
- Abstract: Copyright of Engineering, Technology & Applied Science Research is the property of Engineering, Technology & Applied Science Research and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
- Abstract:
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