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Applied Data Science in Tourism
Engelsk Hardback
SPAR
kr 253
Applied Data Science in Tourism
Engelsk Hardback
Access to large data sets has led to a paradigm shift in the tourism research landscape. Big data is enabling a new form of knowledge gain, while at the same time shaking the epistemological foundations and requiring new methods and analysis approaches. It allows for interdisciplinary cooperation between computer sciences and social and economic sciences, and complements the traditional research approaches. This book provides a broad basis for the practical application of data science approaches such as machine learning, text mining, social network analysis, and many more, which are essential for interdisciplinary tourism research. Each method is presented in principle, viewed analytically, and its advantages and disadvantages are weighed up and typical fields of application are presented. The correct methodical application is presented with a "how-to" approach, together with code examples, allowing a wider reader base including researchers, practitioners, and students entering the field. 

The book is a very well-structured introduction to data science - not only in tourism - and its methodological foundations, accompanied by well-chosen practical cases. It underlines an important insight: data are only representations of reality, you need methodological skills and domain background to derive knowledge from them

Hannes Werthner, Vienna University of Technology
 
Roman Egger has accomplished a difficult but necessary task: make clear how data science can practically support and foster travel and tourism research and applications. The book offers a well-taught collection of chapters giving a comprehensive and deep account of AI and data science for tourism

Francesco Ricci, Free University of Bozen-Bolzano
 
This well-structured and easy-to-read book provides a comprehensive overview of data science in tourism. It contributes largely to the methodological repository beyond traditional methods.

- Rob Law, University of Macau

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Access to large data sets has led to a paradigm shift in the tourism research landscape. Big data is enabling a new form of knowledge gain, while at the same time shaking the epistemological foundations and requiring new methods and analysis approaches. It allows for interdisciplinary cooperation between computer sciences and social and economic sciences, and complements the traditional research approaches. This book provides a broad basis for the practical application of data science approaches such as machine learning, text mining, social network analysis, and many more, which are essential for interdisciplinary tourism research. Each method is presented in principle, viewed analytically, and its advantages and disadvantages are weighed up and typical fields of application are presented. The correct methodical application is presented with a "how-to" approach, together with code examples, allowing a wider reader base including researchers, practitioners, and students entering the field. 

The book is a very well-structured introduction to data science - not only in tourism - and its methodological foundations, accompanied by well-chosen practical cases. It underlines an important insight: data are only representations of reality, you need methodological skills and domain background to derive knowledge from them

Hannes Werthner, Vienna University of Technology
 
Roman Egger has accomplished a difficult but necessary task: make clear how data science can practically support and foster travel and tourism research and applications. The book offers a well-taught collection of chapters giving a comprehensive and deep account of AI and data science for tourism

Francesco Ricci, Free University of Bozen-Bolzano
 
This well-structured and easy-to-read book provides a comprehensive overview of data science in tourism. It contributes largely to the methodological repository beyond traditional methods.

- Rob Law, University of Macau

Produktdetaljer
Sprog: Engelsk
Sider: 608
ISBN-13: 9783030883881
Indbinding: Hardback
Udgave:
ISBN-10: 3030883884
Udg. Dato: 1 feb 2022
Længde: 44mm
Bredde: 163mm
Højde: 243mm
Oplagsdato: 1 feb 2022
Forfatter(e):
Forfatter(e)


Kategori Sandsynlighedsregning og statistik


Sprog Engelsk


Indbinding Hardback


Sider 608


Udgave


Længde 44mm


Bredde 163mm


Højde 243mm


Udg. Dato 1 feb 2022


Oplagsdato 1 feb 2022

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