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Text mining in practice with R / Ted Kwartler

データ種別	電子ブック
出版者	(Hoboken, NJ : John Wiley & Sons)
出版年	2017
大きさ	1 online resource
著者標目	*Kwartler, Ted 1978- author

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URL	巻　次	配架場所	請求記号	登録番号	コメント	刷　年	状　態	利用注記	ISBN	予約	請求メモ
URL		射水-電子	007	EB0005190	Wiley Online Library: Complete oBooks				9781119282099

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一般注記	Includes index What is text mining? -- Basics of text mining -- Common text mining visualizations -- Sentiment scoring -- Hidden structures : clustering, string distance, text vectors & topic modeling -- Document classification : finding clickbait from headlines -- Predictive modeling : using text for classifying & predicting outcomes -- The OpenNLP Project -- Text sources Print version record and CIP data provided by publisher Includes bibliographical references and index 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 John Wiley and Sons Wiley Online Library: Complete oBooks HTTP:URL=https://onlinelibrary.wiley.com/doi/book/10.1002/9781119282105
件　名	LCSH:Data mining LCSH:Text processing (Computer science) MESH:Data Mining MESH:Word Processing CSHF:Exploration de donn�ees (Informatique) CSHF:Traitement de texte FREE:COMPUTERS -- General 全ての件名で検索 FREE:Data mining FREE:Text processing (Computer science) FREE:Internet Resources
分　類	LCC:QA76.9.D343 DC23:006.3/12
書誌ID	EB00004480
ISBN	9781119282099