• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>International Conference on Tools with Artificial Intelligence >TM-Gen: A Topic Map Generator from Text Documents
【24h】

TM-Gen: A Topic Map Generator from Text Documents

机译：TM-Gen：文本文档中的主题图生成器

获取原文
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

The vast amount of text documents stored in digital format is growing at a frantic rhythm each day. Therefore, tools able to find accurate information searching in natural language information repositories are gaining great interest in recent years. In this context, there are especially interesting tools capable of dealing with large amounts of text information and deriving human-readable summaries. However, one step further is to be able not only to summarize, but to extract the knowledge stored in those texts, and even represent it graphically. In this paper we present an architecture to generate automatically a conceptual representation of knowledge stored in a set of text-based documents. For this purpose we have used the topic maps standard and we have developed a method that combines text mining, statistics, linguistic tools, and semantics to obtain a graphical representation of the information contained therein, which can be coded using a knowledge representation language such as RDF or OWL. The procedure is language-independent, fully automatic, self-adjusting, and it does not need manual configuration by the user. Although the validation of a graphic knowledge representation system is very subjective, we have been able to take advantage of an intermediate product of the process to make a experimental validation of our proposals.
机译：每天，以数字格式存储的大量文本文档都以疯狂的节奏增长。因此，近年来，能够在自然语言信息存储库中找到准确信息搜索的工具引起了极大的兴趣。在这种情况下，有一些特别有趣的工具能够处理大量文本信息并得出人类可读的摘要。然而，进一步的步骤不仅是能够总结，而且能够提取存储在这些文本中的知识，甚至可以图形化地表示它。在本文中，我们提出了一种体系结构，该体系结构可自动生成存储在一组基于文本的文档中的知识的概念表示。为此，我们使用了主题地图标准，并开发了一种方法，该方法结合了文本挖掘，统计，语言工具和语义来获取其中包含的信息的图形表示，可以使用诸如RDF或OWL。该过程是独立于语言的，全自动的，可自行调整的，不需要用户手动配置。尽管图形知识表示系统的验证是非常主观的，但我们已经能够利用过程的中间产品来对我们的建议进行实验性验证。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号