信息抽取的关系框架

SIGMOD Rec. Pub Date : 2016-05-09 DOI:10.1145/2935694.2935696

Ronald Fagin, B. Kimelfeld, Frederick Reiss, Stijn Vansummeren

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引用次数: 11

摘要

信息抽取通常是指从文本内容中填充具有预定义底层语义的关系模式的任务。这一任务在与大数据相关的当代计算挑战中普遍存在。在本文中，我们概述了我们在文档生成器方面的工作，文档生成器是一种用于信息提取的关系框架，其灵感来自IBM的SystemT等基于规则的系统。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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A Relational Framework for Information Extraction

Information Extraction commonly refers to the task of populating a relational schema, having predefined underlying semantics, from textual content. This task is pervasive in contemporary computational challenges associated with Big Data. In this article we provide an overview of our work on document spanners--a relational framework for Information Extraction that is inspired by rule-based systems such as IBM's SystemT.

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SIGMOD Rec.

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