Text Mining in Practice with R (Hardcover)
Language: English
Published by John Wiley & Sons Inc, New York, 2017
- Hardcover
- New
Seller: CitiRetail, Stevenage, United KingdomCitiRetail
AbeBooks seller since June 29, 2022
Condition: New
£ 84.99
Quantity: 1 available
Add to basketItem description from seller
Hardcover. A reliable, cost-effective approach to extracting priceless business information from all sources of text Excavating actionable business insights from data is a complex undertaking, and that complexity is magnified by an order of magnitude when the focus is on documents and other text information. This book takes a practical, hands-on approach to teaching you a reliable, cost-effective approach to mining the vast, untold riches buried within all forms of text using R. Author Ted Kwartler clearly describes all of the tools needed to perform text mining and shows you how to use them to identify practical business applications to get your creative text mining efforts started right away. With the help of numerous real-world examples and case studies from industries ranging from healthcare to entertainment to telecommunications, he demonstrates how to execute an array of text mining processes and functions, including sentiment scoring, topic modelling, predictive modelling, extracting clickbait from headlines, and more. Youll learn how to: Identify actionable social media posts to improve customer service Use text mining in HR to identify candidate perceptions of an organisation, match job descriptions with resumes, and more Extract priceless information from virtually all digital and print sources, including the news media, social media sites, PDFs, and even JPEG and GIF image filesMake text mining an integral component of marketing in order to identify brand evangelists, impact customer propensity modelling, and much more Most companies data mining efforts focus almost exclusively on numerical and categorical data, while text remains a largely untapped resource. Especially in a global marketplace where being first to identify and respond to customer needs and expectations imparts an unbeatable competitive advantage, text represents a source of immense potential value. Unfortunately, there is no reliable, cost-effective technology for extracting analytical insights from the huge and ever-growing volume of text available online and other digital sources, as well as from paper documentsuntil now. A reliable, cost-effective approach to extracting priceless business information from all sources of text Excavating actionable business insights from data is a complex undertaking, and that complexity is magnified by an order of magnitude when the focus is on documents and other text information. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. …
Seller Inventory # 9781119282013
- Title
- Text Mining in Practice with R (Hardcover)
- Author
- Ted Kwartler
- Publisher
- John Wiley & Sons Inc, New York
- Publication year
- 2017
- Condition
- new
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 1119282012
- ISBN 13
- 9781119282013
A reliable, cost-effective approach to extracting priceless business information from all sources of text
Excavating actionable business insights from data is a complex undertaking, and that complexity is magnified by an order of magnitude when the focus is on documents and other text information. This book takes a practical, hands-on approach to teaching you a reliable, cost-effective approach to mining the vast, untold riches buried within all forms of text using R.
Author Ted Kwartler clearly describes all of the tools needed to perform text mining and shows you how to use them to identify practical business applications to get your creative text mining efforts started right away. With the help of numerous real-world examples and case studies from industries ranging from healthcare to entertainment to telecommunications, he demonstrates how to execute an array of text mining processes and functions, including sentiment scoring, topic modelling, predictive modelling, extracting clickbait from headlines, and more. You’ll learn how to:
- Identify actionable social media posts to improve customer service
- Use text mining in HR to identify candidate perceptions of an organisation, match job descriptions with resumes, and more
- Extract priceless information from virtually all digital and print sources, including the news media, social media sites, PDFs, and even JPEG and GIF image files
- Make text mining an integral component of marketing in order to identify brand evangelists, impact customer propensity modelling, and much more
Most companies’ data mining efforts focus almost exclusively on numerical and categorical data, while text remains a largely untapped resource. Especially in a global marketplace where being first to identify and respond to customer needs and expectations imparts an unbeatable competitive advantage, text represents a source of immense potential value. Unfortunately, there is no reliable, cost-effective technology for extracting analytical insights from the huge and ever-growing volume of text available online and other digital sources, as well as from paper documents―until now.
"Synopsis" may belong to another edition of this title.
About the Author
TED KWARTLER is a data science instructor at DataCamp.com. He has worked in analytical and executive roles at DataRobot, Liberty Mutual Insurance and Amazon.com.
"About the title" may belong to another edition of this title.
CitiRetail
Stevenage, United Kingdom
AbeBooks seller since June 29, 2022
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