Text pattern visualization for analysis of biology full text and captions

Computational Systems Bioinformatics. CSB2003. Proceedings of the 2003 IEEE Bioinformatics Conference. CSB2003 Pub Date : 2003-08-11 DOI:10.1109/CSB.2003.1227434

Andrea Grimes, R. Futrelle

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引用次数: 3

Abstract

Large textbanks comprised of thousands of full-text biology papers are rapidly becoming available. We describe an approach to characterize all major language patterns in biology text in terms of frameworks. Frameworks are "containers" made up of common phrases surrounding specific informational items such as gene and protein names. A framework viewer has been developed that shows similar text frameworks aligned on the screen much as biosequence visualization tools do. Using the viewer, it is evident that frameworks have the power to find the types of structures needed to develop useful information retrieval systems. As a simple example, one framework was able to concisely select 45,000 nouns from a corpus of 5 million words without error. This work points the way to highly automated systems that will be able to extract and index information in biology textbanks. Work in progress includes extensions to characterize recursive structures in text, subsystems to retrieve figures in papers, and the discovery of semantic relations to aid concept-based retrieval.

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用于生物学全文和标题分析的文本模式可视化

由数千篇全文生物学论文组成的大型文本库正在迅速普及。我们描述了一种方法来表征所有主要的语言模式在生物学文本的框架。框架是由围绕特定信息项(如基因和蛋白质名称)的常用短语组成的“容器”。一个框架查看器已经被开发出来，它可以像生物序列可视化工具那样在屏幕上显示类似的文本框架。使用查看器，很明显框架有能力找到开发有用的信息检索系统所需的结构类型。举个简单的例子，一个框架能够准确无误地从500万个单词的语料库中选择45000个名词。这项工作为高度自动化的系统指明了道路，该系统将能够从生物学教科书库中提取和索引信息。正在进行的工作包括扩展以表征文本中的递归结构，检索论文中的图形的子系统，以及发现语义关系以帮助基于概念的检索。

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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Computational Systems Bioinformatics. CSB2003. Proceedings of the 2003 IEEE Bioinformatics Conference. CSB2003

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