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Dynamic information extraction with self-organizing evidence construction

机译:具有自组织证据构造的动态信息提取

摘要

A data analysis system with dynamic information extraction and self-organizing evidence construction finds numerous applications in information gathering and analysis, including the extraction of targeted information from voluminous textual resources. One disclosed method involves matching text with a concept map to identify evidence relations, and organizing the evidence relations into one or more evidence structures that represent the ways in which the concept map is instantiated in the evidence relations. The text may be contained in one or more documents in electronic form, and the documents may be indexed on a paragraph level of granularity. The evidence relations may self-organize into the evidence structures, with feedback provided to the user to guide the identification of evidence relations and their self-organization into evidence structures. A method of extracting information from one or more documents in electronic form includes the steps of clustering the document into clustered text; identifying patterns in the clustered text; and matching the patterns with the concept map to identify evidence relations such that the evidence relations self-organize into evidence structures that represent the ways in which the concept map is instantiated in the evidence relations.
机译:具有动态信息提取和自组织证据构造功能的数据分析系统在信息收集和分析中有许多应用,包括从大量文本资源中提取目标信息。一种公开的方法涉及将文本与概念图匹配以识别证据关系,并将证据关系组织成一个或多个证据结构,该结构表示在证据关系中实例化概念图的方式。文本可以电子形式包含在一个或多个文档中,并且可以在段落的粒度级别上为这些文档建立索引。证据关系可以自组织为证据结构,并向用户提供反馈以指导证据关系的识别及其自组织为证据结构。一种以电子形式从一个或多个文档中提取信息的方法,包括以下步骤:将文档聚类为聚类文本;识别聚类文本中的模式;使模式与概念图匹配以识别证据关系,从而使证据关系自组织成证据结构,这些结构代表在证据关系中实例化概念图的方式。

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