Text Mining in Practice with R

Ted Kwartler

  • 出版商: Wiley
  • 出版日期: 2017-07-24
  • 定價: $2,600
  • 售價: 9.5$2,470
  • 語言: 英文
  • 頁數: 320
  • 裝訂: Hardcover
  • ISBN: 1119282012
  • ISBN-13: 9781119282013
  • 相關分類: Text-mining
  • 立即出貨 (庫存 < 3)

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商品描述

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. 

商品描述(中文翻譯)

一種可靠且具成本效益的方法,用於從所有文本來源中提取無價的商業信息

從數據中挖掘可行的商業洞察是一項複雜的任務,當焦點放在文件和其他文本信息上時,這種複雜性會成倍增加。本書採用實用的、實踐性的方法,教授您一種可靠且具成本效益的方法,使用 R 來開採各種文本形式中埋藏的巨大財富。

作者 Ted Kwartler 清楚地描述了執行文本挖掘所需的所有工具,並向您展示如何使用這些工具來識別實際的商業應用,以便立即開始進行創造性的文本挖掘工作。通過大量來自醫療保健、娛樂、電信等行業的實際案例和案例研究,他演示了如何執行各種文本挖掘過程和功能,包括情感評分、主題建模、預測建模、從標題中提取點擊誘餌等。您將學到如何:

- 識別可行的社交媒體帖子以改善客戶服務
- 在人力資源中使用文本挖掘,以識別候選人對組織的看法,將職位描述與簡歷匹配等
- 從幾乎所有數字和印刷資源中提取無價的信息,包括新聞媒體、社交媒體網站、PDF 文件,甚至 JPEG 和 GIF 圖像文件
- 將文本挖掘作為市場營銷的一個重要組成部分,以識別品牌傳教士,影響客戶傾向建模等

大多數公司的數據挖掘工作幾乎完全集中在數值和分類數據上,而文本仍然是一個基本未開發的資源。特別是在全球市場上,第一個識別並回應客戶需求和期望的能力帶來了無與倫比的競爭優勢,文本代表著巨大的潛在價值。不幸的是,迄今為止,從在線和其他數字資源以及紙質文件中提取分析洞察的可靠且具成本效益的技術尚未出現。