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Deep Learning Sentiment Analysis of Hotel Reviews with BiLSTM: Deep Learning-Based Sentiment Analysis of Hotel Reviews Using LSTM and Bidirectional LSTM Models - Softcover

Durga Prasad, Kadupu; Duvvuri, Suneel Kumar

 
9786209341229: Deep Learning Sentiment Analysis of Hotel Reviews with BiLSTM: Deep Learning-Based Sentiment Analysis of Hotel Reviews Using LSTM and Bidirectional LSTM Models
Softcover
ISBN 10: 6209341225 ISBN 13: 9786209341229
Verlag: LAP LAMBERT Academic Publishing, 2026

Inhaltsangabe

In the digital era, the rapid growth of online platforms has significantly transformed the hospitality industry, where customer decisions are increasingly influenced by user-generated reviews. These reviews provide valuable insights into customer experiences; however, the vast volume of unstructured textual data makes manual analysis inefficient and impractical. To address this challenge, this study proposes an automated sentiment analysis system using deep learning techniques to classify hotel reviews into positive and negative sentiments.The research utilizes a large-scale dataset comprising over 500,000 hotel reviews, which undergoes extensive preprocessing, including text cleaning, tokenization, stopword removal, and data balancing to ensure model reliability. Exploratory Data Analysis (EDA) is conducted to understand data distribution and extract meaningful patterns. The processed textual data is then transformed into numerical representations using tokenization and sequence padding techniques.Two deep learning models, Long Short-Term Memory (LSTM) and Bidirectional Long ShortTerm Memory (BiLSTM), are implemented to capture sequential dependencies and contextual relationships.

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Über die Autorin bzw. den Autor

Mr. Kadupu Durga Prasad is an M.Sc. Computer Science student at Government College (Autonomous), Rajahmundry. This dissertation was completed under the guidance of Dr. Suneel Kumar Duvvuri, reflecting his academic interest in advanced computing research and practical applications in the field of computer science.

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Verlag
LAP LAMBERT Academic Publishing
Erscheinungsdatum
2026
Sprache
Englisch
ISBN 10 
6209341225
ISBN 13 
9786209341229
Einband
Taschenbuch
Anzahl der Seiten
112
Kontakt zum Hersteller
Editorial Academica Espanola
customerservice@vdm-vsg.de

Brivibas gatve 197
Riga
1039
Lettland