用分块法提取术语

Proceedings of the COLING Workshop on Synchronic and Diachronic Approaches to Analyzing Technical Language Pub Date : 2014-08-24 DOI:10.3115/v1/W14-6002

Adam Meyers, Zachary Glass, Angus B. Grieve-Smith, Yifan He, Shasha Liao, R. Grishman

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引用次数: 6

摘要

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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Jargon-Term Extraction by Chunking

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.

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Proceedings of the COLING Workshop on Synchronic and Diachronic Approaches to Analyzing Technical Language

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