Semi-automatic construction of topic ontologies

被引:0
|
作者
Fortuna, Blaz [1 ]
Mladenic, Dunja [1 ]
Grobelnik, Marko [1 ]
机构
[1] Jozef Stefan Inst, Jamova 39, Ljubljana 1000, Slovenia
来源
SEMANTICS, WEB AND MINING | 2006年 / 4289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
In this paper, we review two techniques for topic discovery in collections of text documents (Latent Semantic Indexing and K-Means clustering) and present how we integrated them into a system for semiautomatic topic ontology construction. The OntoGen system offers support to the user during the construction process by suggesting topics and analyzing them in real time. It suggests names for the topics in two alternative ways both based on extracting keywords from a set of documents inside the topic. The first set of descriptive keyword is extracted using document centroid vectors, while the second set of distinctive keyword is extracted from the SVM classification model dividing documents in the topic from the neighboring documents.
引用
收藏
页码:121 / 131
页数:11
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