OPTIMIZING Optimizing hidden layers in LSTM networks to generate detailed summaries of hotel reviews
DOI:
https://doi.org/10.61591/jslhu.20.623Keywords:
Sentiment analysis; Deep neural network; LSTM; Hotel review.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.
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