文本关系自动提取研究进展

Kun Li, Junsheng Zhang, Changqing Yao, Chongde Shi
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引用次数: 4

摘要

关系提取是文本理解的重要环节。在大数据时代,从非结构化文本中自动提取关系是结构化信息组织和信息分析的迫切需要。本文综述了在封闭数据集和开放信息环境(如Web)下的自动关系提取方法,特别是传统的机器学习方法,包括监督和半监督方法。然后讨论了基于关系抽取的应用,如事件抽取和QA系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automatic Relation Extraction from Text: A Survey
Relation extraction is an important task for understanding text. In the big data era, automatic relation extraction from unstructured texts is urgently needed for structured information organization and information analysis. In this paper, we survey the automatic relation extraction methods, especially the traditional machine learning on closed data set and open information environment such as Web, including supervised and semi-supervised methods. And then, we discuss the applications based on relation extraction such as event extraction and QA systems.
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