Event recognition on news stories and semi-automatic population of an ontology

被引：17
|
作者：
Vargas-Vera, M [1 ]
Celjuska, D [1 ]
机构：
[1] Open Univ, Knowledge Media Inst, Milton Keynes MK7 6AA, Bucks, England
来源：
IEEE/WIC/ACM INTERNATIONAL CONFERENCE ON WEB INTELLIGENCE (WI 2004), PROCEEDINGS | 2004年
关键词：
D O I：
10.1109/WI.2004.10148
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper describes a system which recognizes events on news stories. Our system classifies stories and populates a hand-crafted ontology with new instances of classes defined in it. Currently, our system recognizes events which can be classified as belonging to a single category and it also recognizes overlapping events within one article (more than one event is recognized). In each case, the system provides a confidence value associated to the suggested classification. Our system uses Information Extraction and Machine Learning technologies. The system was tested using a corpus of 200 news articles from an archive of electronic news stories describing the academic life of the Knowledge Media (KMi). In particular, these news stories describe events such as a project award, publications, visits, etc).
引用
收藏
页码：615 / 618
页数：4
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