Fundamentals of Predictive Text Mining (Texts in Computer Science)

Sholom M. M. Weiss

  • 出版商: Springer
  • 出版日期: 2016-10-29
  • 售價: $2,350
  • 貴賓價: 9.5$2,233
  • 語言: 英文
  • 頁數: 256
  • 裝訂: Paperback
  • ISBN: 1447171136
  • ISBN-13: 9781447171133
  • 相關分類: Text-miningComputer-ScienceMachine Learning
  • 海外代購書籍(需單獨結帳)

商品描述

This successful textbook on predictive text mining offers a unified perspective on a rapidly evolving field, integrating topics spanning the varied disciplines of data science, machine learning, databases, and computational linguistics. Serving also as a practical guide, this unique book provides helpful advice illustrated by examples and case studies. This highly anticipated second edition has been thoroughly revised and expanded with new material on deep learning, graph models, mining social media, errors and pitfalls in big data evaluation, Twitter sentiment analysis, and dependency parsing discussion. The fully updated content also features in-depth discussions on issues of document classification, information retrieval, clustering and organizing documents, information extraction, web-based data-sourcing, and prediction and evaluation. Features: includes chapter summaries and exercises; explores the application of each method; provides several case studies; contains links to free text-mining software.

商品描述(中文翻譯)

這本成功的預測性文本挖掘教科書提供了對一個快速發展的領域的統一觀點,整合了數據科學、機器學習、數據庫和計算語言學等多個學科的主題。作為一本實用指南,這本獨特的書籍提供了以例子和案例研究為例的有用建議。這本備受期待的第二版已經經過全面修訂和擴充,新增了關於深度學習、圖模型、社交媒體挖掘、大數據評估中的錯誤和陷阱、Twitter情感分析和依存句法分析討論的新內容。全面更新的內容還深入討論了文件分類、信息檢索、文件分類和組織、信息提取、基於網絡的數據採集以及預測和評估等問題。特點:包括章節摘要和練習題;探討每種方法的應用;提供多個案例研究;包含免費文本挖掘軟件的鏈接。