Deep Learning Sentiment Analysis by Durga Prasad (9 results)

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Taschenbuch. Condition: Neu. Deep Learning Sentiment Analysis of Hotel Reviews with BiLSTM | Deep Learning-Based Sentiment Analysis of Hotel Reviews Using LSTM and Bidirectional LSTM Models | Kadupu Durga Prasad (u. a.) | Taschenbuch | Englisch | 2026 | LAP LAMBERT Academic Publishing | EAN 9786209341229 | Verantwortliche Person… für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu.

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Paperback. Condition: new. Paperback. 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 unst…ructured 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. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Language: English
Published by LAP LAMBERT Academic Publishing Apr 2026, 2026
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 112 pp. Englisch.

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Paperback. Condition: new. Paperback. 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 unst…ructured 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. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Language: English
Published by LAP LAMBERT Academic Publishing Apr 2026, 2026
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Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germanybuchversandmimpf2000
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