Big Data analytics and machine learning are being adopted in a range of industries – but how can these technologies be utilised and what can they offer to the tourism industry? In the process of their journeys and in their decision-making processes, people who travel contribute to the generation of a huge flow of data; all this information is a potential base for creating smart destinations and improving tourism organizations’ potential to customize their products and service offerings.
The real execution of such inventive forms of data-driven value generation in tourism continues to be more restricted to the theory or used in a few exceptional cases. Big data and machine learning techniques in tourism persists as an unclear concept and a subject of investigation that necessitates closer analysis from an extensive range of field and research methods. Big Data Analytics for the Prediction of Tourist Preferences Worldwide tackles this challenge, exploring the benefits, importance and demonstrates how Big Data can be applied in predicting tourist preferences and delivering tourism services in a customer friendly manner.
The authors provide theoretical and experiential contributions designed to see a wider adoption of these technologies in the tourism industry.
"synopsis" may belong to another edition of this title.
Dr. N. Padmaja is Assistant Professor at the Department of Computer Science and Engineering, SRI Padmavati Mahila Visvavidyalayam, India.
Dr. Rajalakshmi Subramaniam is the Founder and CEO at Talaash Research Consultants, Chennai, India.
Dr. Sanjay Mohapatra is Director of Research at Batoi Systems Pvt Ltd, India.
"About this title" may belong to another edition of this title.
FREE shipping within United Kingdom
Destination, rates & speedsSeller: GreatBookPricesUK, Woodford Green, United Kingdom
Condition: New. Seller Inventory # 47098151-n
Quantity: Over 20 available
Seller: PBShop.store UK, Fairford, GLOS, United Kingdom
HRD. Condition: New. New Book. Shipped from UK. Established seller since 2000. Seller Inventory # FW-9781835493397
Quantity: 15 available
Seller: THE SAINT BOOKSTORE, Southport, United Kingdom
Hardback. Condition: New. New copy - Usually dispatched within 4 working days. 298. Seller Inventory # B9781835493397
Quantity: Over 20 available
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Condition: New. In. Seller Inventory # ria9781835493397_new
Quantity: Over 20 available
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Condition: As New. Unread book in perfect condition. Seller Inventory # 47098151
Quantity: Over 20 available
Seller: Majestic Books, Hounslow, United Kingdom
Condition: New. Seller Inventory # 397421778
Quantity: 3 available
Seller: CitiRetail, Stevenage, United Kingdom
Hardcover. Condition: new. Hardcover. Big Data analytics and machine learning are being adopted in a range of industries - but how can these technologies be utilised and what can they offer to the tourism industry? In the process of their journeys and in their decision-making processes, people who travel contribute to the generation of a huge flow of data; all this information is a potential base for creating smart destinations and improving tourism organizations' potential to customize their products and service offerings.The real execution of such inventive forms of data-driven value generation in tourism continues to be more restricted to the theory or used in a few exceptional cases. Big data and machine learning techniques in tourism persists as an unclear concept and a subject of investigation that necessitates closer analysis from an extensive range of field and research methods. Big Data Analytics for the Prediction of Tourist Preferences Worldwide tackles this challenge, exploring the benefits, importance and demonstrates how Big Data can be applied in predicting tourist preferences and delivering tourism services in a customer friendly manner.The authors provide theoretical and experiential contributions designed to see a wider adoption of these technologies in the tourism industry. Big Data Analytics for the Prediction of Tourist Preferences Worldwide explores the benefits, importance and demonstrates how Big Data can be applied in predicting tourist preferences and delivering tourism services in a customer friendly manner. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9781835493397
Quantity: 1 available
Seller: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Ireland
Condition: New. Seller Inventory # V9781835493397
Quantity: Over 20 available
Seller: Revaluation Books, Exeter, United Kingdom
Hardcover. Condition: Brand New. 172 pages. 9.02x5.98x0.38 inches. In Stock. This item is printed on demand. Seller Inventory # __1835493394
Quantity: 2 available
Seller: Rarewaves USA United, OSWEGO, IL, U.S.A.
Hardback. Condition: New. Big Data analytics and machine learning are being adopted in a range of industries - but how can these technologies be utilised and what can they offer to the tourism industry? In the process of their journeys and in their decision-making processes, people who travel contribute to the generation of a huge flow of data; all this information is a potential base for creating smart destinations and improving tourism organizations' potential to customize their products and service offerings.The real execution of such inventive forms of data-driven value generation in tourism continues to be more restricted to the theory or used in a few exceptional cases. Big data and machine learning techniques in tourism persists as an unclear concept and a subject of investigation that necessitates closer analysis from an extensive range of field and research methods. Big Data Analytics for the Prediction of Tourist Preferences Worldwide tackles this challenge, exploring the benefits, importance and demonstrates how Big Data can be applied in predicting tourist preferences and delivering tourism services in a customer friendly manner.The authors provide theoretical and experiential contributions designed to see a wider adoption of these technologies in the tourism industry. Seller Inventory # LU-9781835493397
Quantity: Over 20 available