Optimizing hidden layers in LSTM networks to generate detailed summaries of hotel reviews

Online hotel booking platforms often lack the ability to provide detailed summaries of user reviews across key service areas, such as food, accommodation, service quality, and location. This study introduces a breakthrough solution using Long Short-Term Memory (LSTM) networks with optimized hidden layer configurations. With an F1- score of 75.28%—an increase of 10.18% compared to the standard LSTM model—the model has proven effective in generating review summaries for specific aspects. This advancement offers users a smarter and more efficient hotel booking experience while addressing the limitations of current review systems.

Authors

Publication Details

Journal
Tạp chí Khoa học Lạc Hồng
Published
2025-05-22
DOI
https://doi.org/10.61591/jslhu.20.623
Primary Topic
Digital Marketing and Social Media
Type
article
Field-Weighted Citation Impact
0.00
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article

Optimizing hidden layers in LSTM networks to generate detailed summaries of hotel reviews

Lei Bao, Nguyen Thanh Son, Le Phuong Long, Dang Dang Khoa
Tạp chí Khoa học Lạc Hồng
Digital Marketing and Social Media
article

Optimizing hidden layers in LSTM networks to generate detailed summaries of hotel reviews

Lei Bao, Nguyen Thanh Son, Le Phuong Long, Dang Dang Khoa
article en

Abstract

Online hotel booking platforms often lack the ability to provide detailed summaries of user reviews across key service areas, such as food, accommodation, service quality, and location. This study introduces a breakthrough solution using Long Short-Term Memory (LSTM) networks with optimized hidden layer configurations. With an F1- score of 75.28%—an increase of 10.18% compared to the standard LSTM model—the model has proven effective in generating review summaries for specific aspects. This advancement offers users a smarter and more efficient hotel booking experience while addressing the limitations of current review systems.

Tạp chí Khoa học Lạc HồngVol. 1(20)
Openalex Percentile: Top 85%
Digital Marketing and Social Media
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