Event Recognition on News Stories and Semi-Automatic Population of an Ontology
(2004) Event Recognition on News Stories and Semi-Automatic Population of an Ontology. In Proceedings International Conference on Web Intelligence (WI 2004)., Beijing, China..
This document is not available online.
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.)
| Keywords: | Event recognition, Information Extraction, Ontology population, Natural Language Processing, Machine Learning |
|---|---|
| Subjects: | AKT Challenges > Knowledge acquisition |
| ID Code: | 341 |
| Deposited By: | Vargas-Vera, Dr Maria |
| Deposited On: | 29 June 2004 |
| Alternative Locations: | ttp://kmi.open.ac.uk/publications/papers/KMI-TR-149.pdf |
Contact the site administrator at: hg@ecs.soton.ac.uk