Jargon-Term Extraction by Chunking

Adam Meyers, Zachary Glass, Angus B. Grieve-Smith, Yifan He, Shasha Liao, R. Grishman
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引用次数: 6

Abstract

NLP definitions of Terminology are usually application-dependent. IR terms are noun sequences that characterize topics. Terms can also be arguments for relations like abbreviation, definition or IS-A. In contrast, this paper explores techniques for extracting terms fitting a broader definition: noun sequences specific to topics and not well-known to naive adults. We describe a chunkingbased approach, an evaluation, and applications to non-topic-specific relation extraction.
用分块法提取术语
术语的NLP定义通常依赖于应用。IR术语是描述主题的名词序列。术语也可以作为诸如缩写、定义或IS-A等关系的参数。相比之下,本文探讨了提取符合更广泛定义的术语的技术:特定于主题的名词序列,不为幼稚的成年人所熟知。我们描述了一种基于分块的方法,一种评估方法,以及在非主题特定关系提取中的应用。
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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