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Wineinformatics = a new data science...

Chen, Bernard.

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Wineinformatics = a new data science application /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Wineinformatics/ by Bernard Chen.
Reminder of title:	a new data science application /
Author:	Chen, Bernard.
Published:	Singapore :Springer Nature Singapore : : 2023.,
Description:	ix, 69 p. :ill., digital ;24 cm.
[NT 15003449]:	Chapter 1 Introduction -- Chapter 2 Data collection and preprocessing -- Chapter 3 Classification in Wineinformatics -- Chapter 4 Regression on Wine Prediction -- Chapter 5 Analysis on Wine Reviewers -- Chapter 6 Advanced Application of the Computational Wine Wheel -- Chapter 7 Conclusion and Future Works.
Contained By:	Springer Nature eBook
Subject:	Wine and wine making - Data processing. -
Online resource:	https://doi.org/10.1007/978-981-19-7369-7
ISBN:	9789811973697

Wineinformatics = a new data science application /
Chen, Bernard.

Wineinformaticsa new data science application /[electronic resource] :by Bernard Chen. - Singapore :Springer Nature Singapore :2023. - ix, 69 p. :ill., digital ;24 cm. - SpringerBriefs in computer science,2191-5776. - SpringerBriefs in computer science..

Chapter 1 Introduction -- Chapter 2 Data collection and preprocessing -- Chapter 3 Classification in Wineinformatics -- Chapter 4 Regression on Wine Prediction -- Chapter 5 Analysis on Wine Reviewers -- Chapter 6 Advanced Application of the Computational Wine Wheel -- Chapter 7 Conclusion and Future Works.

Wineinformatics is a new data science application with a focus on understanding wine through artificial intelligence. Thousands of new wine reviews are produced monthly, which benefits the understanding of wine through wine experts for winemakers and consumers. This book systematically investigates how to process human language format reviews and mine useful knowledge from a large volume of processed data. This book presents a human language processing tool named Computational Wine Wheel to process professional wine reviews and three novel Wineinformatics studies to analyze wine quality, price and reviewers. Through the lens of data science, the author demonstrates how the wine receives 90+ scores out of 100 points from Wine Spectator, how to predict a wine's specific grade and price through wine reviews and how to rank a group of wine reviewers. The book also shows the advanced application of the Computational Wine Wheel to capture more information hidden in wine reviews and the possibility of extending the wheel to coffee, tea beer, sake and liquors. This book targets computer scientists, data scientists and wine industrial researchers, who are interested in Wineinformatics. Senior data science undergraduate and graduate students may also benefit from this book.

ISBN: 9789811973697

Standard No.: 10.1007/978-981-19-7369-7doiSubjects--Topical Terms:

3625350
Wine and wine making
--Data processing.

LC Class. No.: TP548

Dewey Class. No.: 641.22028563

Wineinformatics = a new data science application /
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520 $a Wineinformatics is a new data science application with a focus on understanding wine through artificial intelligence. Thousands of new wine reviews are produced monthly, which benefits the understanding of wine through wine experts for winemakers and consumers. This book systematically investigates how to process human language format reviews and mine useful knowledge from a large volume of processed data. This book presents a human language processing tool named Computational Wine Wheel to process professional wine reviews and three novel Wineinformatics studies to analyze wine quality, price and reviewers. Through the lens of data science, the author demonstrates how the wine receives 90+ scores out of 100 points from Wine Spectator, how to predict a wine's specific grade and price through wine reviews and how to rank a group of wine reviewers. The book also shows the advanced application of the Computational Wine Wheel to capture more information hidden in wine reviews and the possibility of extending the wheel to coffee, tea beer, sake and liquors. This book targets computer scientists, data scientists and wine industrial researchers, who are interested in Wineinformatics. Senior data science undergraduate and graduate students may also benefit from this book.
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