ASTAS: Elevating Hospitality Insights Through Transformer-Based Aspect Analysis and Opinion Summarization

The chapter explores the critical role of customer feedback in the hospitality industry, highlighting the potential of advanced natural language processing (NLP) techniques to transform textual reviews into actionable insights. It introduces a hybrid model named ASTAS, which integrates DistilBERT for sentiment analysis and T5 for opinion summarization, enabling a detailed understanding of customer sentiments regarding various hotel services. The study demonstrates the superior performance of ASTAS in sentiment classification and opinion summarization, offering a robust framework for improving service quality and guest satisfaction. The chapter also provides a comprehensive overview of related works, methodology, and experimental setup, including data collection, preprocessing, and evaluation metrics. It discusses the strengths and limitations of the proposed model, suggesting avenues for future research and practical applications in real-world scenarios. The detailed analysis and innovative approach make this chapter an essential read for anyone interested in leveraging NLP for data-driven decision-making in the hospitality sector.