Terminology-driven literature mining and knowledge acquisition in biomedicine
Terminology-driven literature mining and knowledge acquisition in biomedicine
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DOI：
10.1016/s1386-5056(02)00055-2
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发表时间：
2002-12-04
影响因子：
4.9
通讯作者：
Tsujii, J
中科院分区：
文献类型：
--
作者：
Nenadic, G;Mima, H;Tsujii, J
在本文中，我们描述了标签信息管理系统（TIMS），一个集成的知识管理系统的分子生物学和生物医学领域，在其中的术语驱动的文献挖掘，知识获取（KA），知识集成（KI），和基于XML的知识检索相结合，使用标签信息管理和本体推理。该系统集成了术语自动获取、术语变异管理、层次术语聚类、基于标签的信息抽取和基于本体的查询扩展等功能。TIMS支持引入和组合不同类型的标签（语言和特定领域，手动和自动）。引入了基于标记的区间操作和查询语言，以方便KA和从XML文档中检索。通过KA实例，说明了文献挖掘的方法。技术可以用于从文档中发现知识。(C)2002爱思唯尔科学爱尔兰有限公司保留所有权利。
In this paper we describe Tagged Information Management System (TIMS), an integrated knowledge management system for the domain of molecular biology and biomedicine, in which terminology-driven literature mining, knowledge acquisition (KA), knowledge integration (KI), and XML-based knowledge retrieval are combined using tag information management and ontology inference. The system integrates automatic terminology acquisition, term variation management, hierarchical term clustering, tag-based information extraction (IE), and ontology-based query expansion. TIMS supports introducing and combining different types of tags (linguistic and domain-specific, manual and automatic). Tag-based interval operations and a query language are introduced in order to facilitate KA and retrieval from XML documents. Through KA examples, we illustrate the way in which literature mining. techniques can be utilised for knowledge discovery from documents. (C) 2002 Elsevier Science Ireland Ltd. All rights reserved.