Linguistic Summaries of Static and Dynamic Data: Computing with Words and Granularity

J. Kacprzyk
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引用次数: 3

Abstract

Summary form only given. First, we briefly advocate a need of natural language based methods in data mining, notably whew domain experts have a limited knowledge of modern tools of information technology. We present some approaches to linguistic summarization of sets of (numeric and/or textual) data, and show that a fuzzy logic based approach by Yager (1982), notably in its extended and implementable version of Kacprzyk and Yager (2001), and Kacprzyk, Yager and Zadrozny (2000), offers a simplicity and intuitive appeal, in particular in its new setting by Kacprzyk and Zadrozny (2005) based on Zadeh's computing with words and protoforms.
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静态和动态数据的语言摘要:用词和粒度计算
只提供摘要形式。首先,我们简要地提倡在数据挖掘中需要基于自然语言的方法,特别是当领域专家对现代信息技术工具的了解有限时。我们提出了一些对(数字和/或文本)数据集进行语言总结的方法,并表明Yager(1982)基于模糊逻辑的方法,特别是在Kacprzyk和Yager(2001)以及Kacprzyk, Yager和Zadrozny(2000)的扩展和可实现版本中,提供了简单和直观的吸引力,特别是在Kacprzyk和Zadrozny(2005)基于Zadeh的单词和原型计算的新设置中。
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