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• W4318818317 abstract "Over the last decade, tourism industry is exploring the latest technologies to improve the customer experience and enhance customer satisfaction. In order to address the customer demands and business, tourism industry embraces to redefine their products and services using deep learning models and big data analytics. Deep learning-based model can be used to measure customer satisfaction, perception and behavior utilizing sentiment analysis, emotion analysis, and data analysis. Big data analytics in tourism can improve the overall tourism business operations and services. Deep learning techniques with big data analytics not only helps in developing the economical tourism models but also analyze the impact of various environmental factors on tourism planning and travel demand. In addition, these techniques are helpful in estimation of tourist seasonal demands, market price strategies and data analysis automation. Deep learning using data analytics can bring a paradigm shift in the tourism industry by offering personalized recommendations with budget specific packages based on customer past travel, reviews and experience. In this chapter, we will briefly analyze the impact of deep learning in tourism sector in terms of innovation, commercialization and profitability of the business. In addition, we will also review the advancement and potential of the deep learning-based methods with big data analytics in tourism industry in terms of customer overall experience." @default.
• W4318818317 created "2023-02-02" @default.
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• W4318818317 date "2023-01-01" @default.
• W4318818317 modified "2023-10-14" @default.
• W4318818317 title "Impact of Deep Learning Models for Technology Sustainability in Tourism Using Big Data Analytics" @default.
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• W4318818317 doi "https://doi.org/10.1007/978-981-19-5723-9_6" @default.
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