管理提取信息的未来趋势

W. Yafooz, S. Z. Abidin, N. Omar, Zanariah Idrus
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引用次数: 2

摘要

Web技术目前被用于所有的日常活动中,被认为是生活的支柱。信息的数量不断增加和增长,特别是那些没有规则或约束的非结构化信息。这些信息很难处理,因此需要组织和管理才能发挥作用。信息提取技术是将非结构化文档转换为结构化数据的有效方法。已经尝试提取可以与少量文本数据一起使用的结构化信息。然而,对于大量的数据,如在万维网中发现的数据,提取的信息量是巨大的,并且提取的信息之间的关系很难确定。专注于管理提取信息的研究很少。本文综述了近年来在非结构化信息管理、信息抽取和抽取信息管理方面的研究进展。强调了使用我们提出的模型来管理提取的数据,以便为关系数据库系统的底层后端应用程序快速提取和聚类非结构化数据。本文面向对信息抽取管理及其应用感兴趣的研究人员。
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Future trends in managing extracted information
Web technology is currently used in all daily activities and is considered a backbone of life. The amount of information continuously increases and grows, specifically that of unstructured information that has no rules or constraints. Such information is difficult to handle and thus requires organization and management before it can be useful. Information extraction techniques are efficient methods of converting unstructured documents into structured data. Attempts have been made to extract structured information that can be used with small amounts of textual data. However, for large amounts of data such as those found in the World Wide Web, the amount of extracted information is huge, and the relationships between extracted information are difficult to determine. Studies that focus on managing extracted information are few. In this paper, we present an overview of the recent studies on managing unstructured information, information extraction and managing extracted information. Managing extracted data using our proposed model for the rapid extraction and clustering of unstructured data for back-end applications in low-level of relational database systems is highlighted. This paper is intended for researchers interested in information extraction management and its applications.
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