The Open UniversitySkip to content
 

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

Vargas-Vera, Maria and Celjuska, David (2004). Event recognition on news stories and semi-automatic population of an ontology. In: Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence (WI'04), 20-24 Sep 2004, Beijing, China, ieee publishing house.

Full text available as:
[img]
Preview
PDF (Not Set) - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
Download (187Kb)
DOI (Digital Object Identifier) Link: http://doi.org/10.1109/WI.2004.65
Google Scholar: Look up in Google Scholar

Abstract

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.)

Item Type: Conference Item
Academic Unit/Department: Mathematics, Computing and Technology > Computing & Communications
Mathematics, Computing and Technology
Item ID: 2995
Depositing User: Users 12 not found.
Date Deposited: 26 Jun 2006
Last Modified: 23 Feb 2016 21:25
URI: http://oro.open.ac.uk/id/eprint/2995
Share this page:

Altmetrics

Scopus Citations

► Automated document suggestions from open access sources

Download history for this item

These details should be considered as only a guide to the number of downloads performed manually. Algorithmic methods have been applied in an attempt to remove automated downloads from the displayed statistics but no guarantee can be made as to the accuracy of the figures.

Actions (login may be required)

Policies | Disclaimer

© The Open University   + 44 (0)870 333 4340   general-enquiries@open.ac.uk