Text Data Management and Analysis: A Practical Introduction to Information Retrieval and Text Mining

ChengXiang Zhai, Sean Massung

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商品描述

Recent years have seen a dramatic growth of natural language text data, including web pages, news articles, scientific literature, emails, enterprise documents, and social media such as blog articles, forum posts, product reviews, and tweets. This has led to an increasing demand for powerful software tools to help people analyze and manage vast amounts of text data effectively and efficiently. Unlike data generated by a computer system or sensors, text data are usually generated directly by humans, and are accompanied by semantically rich content. As such, text data are especially valuable for discovering knowledge about human opinions and preferences, in addition to many other kinds of knowledge that we encode in text. In contrast to structured data, which conform to well-defined schemas (thus are relatively easy for computers to handle), text has less explicit structure, requiring computer processing toward understanding of the content encoded in text. The current technology of natural language processing has not yet reached a point to enable a computer to precisely understand natural language text, but a wide range of statistical and heuristic approaches to analysis and management of text data have been developed over the past few decades. They are usually very robust and can be applied to analyze and manage text data in any natural language, and about any topic.

This book provides a systematic introduction to all these approaches, with an emphasis on covering the most useful knowledge and skills required to build a variety of practically useful text information systems. The focus is on text mining applications that can help users analyze patterns in text data to extract and reveal useful knowledge. Information retrieval systems, including search engines and recommender systems, are also covered as supporting technology for text mining applications. The book covers the major concepts, techniques, and ideas in text data mining and information retrieval from a practical viewpoint, and includes many hands-on exercises designed with a companion software toolkit (i.e., MeTA) to help readers learn how to apply techniques of text mining and information retrieval to real-world text data and how to experiment with and improve some of the algorithms for interesting application tasks. The book can be used as a textbook for a computer science undergraduate course or a reference book for practitioners working on relevant problems in analyzing and managing text data.

商品描述(中文翻譯)

近年來,自然語言文本數據呈現出劇增的趨勢,包括網頁、新聞文章、科學文獻、電子郵件、企業文件以及社交媒體上的博客文章、論壇帖子、產品評論和推文等。這導致對強大的軟體工具的需求增加,以幫助人們有效且高效地分析和管理大量的文本數據。與由計算機系統或傳感器生成的數據不同,文本數據通常是由人類直接生成的,並且伴隨著豐富的語義內容。因此,文本數據對於發現有關人類觀點和偏好的知識尤其有價值,除了其他我們在文本中編碼的知識之外。與結構化數據相比,結構不明確的文本需要計算機處理以理解其中編碼的內容。目前的自然語言處理技術尚未達到使計算機能夠精確理解自然語言文本的程度,但在過去幾十年中,已經開發出了各種統計和啟發式方法來分析和管理文本數據。這些方法通常非常強大,可以應用於分析和管理任何自然語言的文本數據,以及任何主題。

本書系統地介紹了所有這些方法,重點是涵蓋構建各種實用的文本信息系統所需的最有用的知識和技能。重點是文本挖掘應用,可以幫助用戶分析文本數據中的模式,提取和揭示有用的知識。信息檢索系統,包括搜索引擎和推薦系統,也作為文本挖掘應用的支持技術進行介紹。本書從實用的角度介紹了文本數據挖掘和信息檢索的主要概念、技術和思想,並包含許多實踐練習,配有一個附帶的軟體工具包(即MeTA),幫助讀者學習如何應用文本挖掘和信息檢索技術處理真實世界的文本數據,以及如何實驗和改進一些有趣的應用任務的算法。本書可作為計算機科學本科課程的教材,或作為從事分析和管理文本數據相關問題的從業人員的參考書。