Mining the Talk: Unlocking the Business Value in Unstructured Information
暫譯: 挖掘對話:解鎖非結構化資訊中的商業價值
Scott Spangler, Jeffrey Kreulen
- 出版商: IBM Press
- 出版日期: 2007-07-01
- 售價: $1,825
- 貴賓價: 9.5 折 $1,734
- 語言: 英文
- 頁數: 240
- 裝訂: Paperback
- ISBN: 0132339536
- ISBN-13: 9780132339537
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相關分類:
大數據 Big-data、Text-mining、Data Science
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商品描述
Description
This is the first book to provide techniques and approaches for mining knowledge from unstructured business information and the business value of this analysis. Mining the Talk describes a fundamentally new approach to mining knowledge from unstructured business information. This unstructured information in "free form text" that the authors refer to as "talk". It's simply the way humans have been communicating with each other for thousands of years, and it's the most prevalent kind of data to be found. Potentially, its also the most valuable, because hidden inside the talk is little bits and pieces of important information, which if aggregated and summarized could communicate actionable intelligence about how any business is running, how its customers and employees perceive it, what is going right and what is going wrong, and possibly solutions to the most pressing problems the business faces. These are examples of the gold that is waiting to be discovered if business can only "Mine the Talk". The primary methodology employed centers on the creation of natural classifications (taxonomies) of the data objects. The book illustrates that the only way to insure the "naturalness" of taxonomies is through expert human intervention at every stage of the taxonomy generation and modeling process. After giving a high level overview the approach, the book dives into a series of real world examples showing how the mining techniques work in practice.
商品描述(中文翻譯)
**描述**
這是第一本提供從非結構化商業資訊中挖掘知識的技術和方法,以及這種分析的商業價值的書籍。《挖掘對話》描述了一種從非結構化商業資訊中挖掘知識的全新方法。這些非結構化資訊以「自由格式文本」的形式存在,作者稱之為「對話」。這正是人類數千年來彼此溝通的方式,也是最常見的數據類型。潛在地,它也是最有價值的,因為在對話中隱藏著一些重要資訊的片段,如果能夠聚合和總結,將能夠傳達有關任何企業運作的可行情報,包括其客戶和員工的看法、運作良好的地方和存在問題的地方,以及可能的解決方案來應對企業面臨的最緊迫問題。這些都是等待被發現的金礦,只要企業能夠「挖掘對話」。主要的方法論集中在數據對象的自然分類(分類法)的創建上。書中說明,確保分類法的「自然性」的唯一方法是在分類法生成和建模過程的每個階段進行專家的人工干預。在提供方法的高層次概述後,書中深入探討了一系列現實世界的例子,展示了挖掘技術在實踐中的運作方式。