Discovery of lexical entries for non-taxonomic relations in ontology learning

被引：0
|
作者：
Kavalec, M
Maedche, A
Svátek, V
机构：
[1] Univ Econ, Dept Informat & Knowledge Engn, Prague 13067 3, Czech Republic
[2] Robert Bosch GmbH, D-70469 Stuttgart, Germany
来源：
SOFSEM 2004: THEORY AND PRACTICE OF COMPUTER SCIENCE, PROCEEDINGS | 2004年 / 2932卷
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Ontology learning from texts has recently been proposed as a new technology helping ontology designers in the modelling process. Discovery of non-taxonomic relations is understood as the least tackled problem therein. We propose a technique for extraction of lexical entries that may give cue in assigning semantic labels to otherwise 'anonymous' relations. The technique has been implemented as extension to the existing Text-to-Onto tool, and tested on a collection of texts describing worldwide geographic locations from a tour-planning viewpoint.
引用
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页码：249 / 256
页数：8
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