Text Mining and Visualization: Case Studies Using Open-Source Tools (Hardcover)

Text Mining and Visualization: Case Studies Using Open-Source Tools provides an introduction to text mining using some of the most popular and powerful open-source tools: KNIME, RapidMiner, Weka, R, and Python.

The contributors―all highly experienced with text mining and open-source software―explain how text data are gathered and processed from a wide variety of sources, including books, server access logs, websites, social media sites, and message boards. Each chapter presents a case study that you can follow as part of a step-by-step, reproducible example. You can also easily apply and extend the techniques to other problems. All the examples are available on a supplementary website.

The book shows you how to exploit your text data, offering successful application examples and blueprints for you to tackle your text mining tasks and benefit from open and freely available tools. It gets you up to date on the latest and most powerful tools, the data mining process, and specific text mining activities.

《Text Mining and Visualization: Case Studies Using Open-Source Tools》是一本介紹使用一些最受歡迎和強大的開源工具進行文本挖掘的書籍，包括KNIME、RapidMiner、Weka、R和Python。

這些貢獻者都是在文本挖掘和開源軟件方面具有豐富經驗的專家，他們解釋了如何從各種來源（包括書籍、伺服器訪問日誌、網站、社交媒體和留言板）收集和處理文本數據。每一章都提供了一個案例研究，您可以按照逐步可重複的示例進行操作。您還可以輕鬆應用和擴展這些技術來解決其他問題。所有示例都可以在附加網站上找到。

本書向您展示如何利用文本數據，提供成功的應用實例和藍圖，讓您解決文本挖掘任務並從開放且免費的工具中受益。它使您了解最新和最強大的工具、數據挖掘過程和特定的文本挖掘活動。