模糊本体中的概念默认值

2016 Annual Conference of the North American Fuzzy Information Processing Society (NAFIPS) Pub Date : 2016-10-01 DOI:10.1109/NAFIPS.2016.7851606

Julia Taylor Rayz, V. Raskin

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引用次数: 4

摘要

本文探讨了自然语言文本中隐含信息的模糊状态，重点关注概念默认，即读者/听者同样习惯性地重建的习惯性遗漏信息。将这些信息提供给自然语言处理计算机是至关重要的，而模糊性是一个主要问题。一项对1000个英语句子的分析显示了检测和计算默认值及其隶属函数值的多种情况组合。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Conceptual defaults in fuzzy ontology

The paper explores the fuzzy status of implicit information in natural language text, focusing on conceptual defaults, the routinely omitted information that readers/hearers equally routinely reconstruct. Making this information available to the natural language processing computer is essential, and fuzziness is a major issue. An analysis of 1,000 English sentences has demonstrated a diverse combination of circumstances for detecting and computing defaults with their membership function values.

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2016 Annual Conference of the North American Fuzzy Information Processing Society (NAFIPS)

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