Applications of circumscription to formalizing common-sense knowledge
Artificial Intelligence
The automatic identification of stop words
Journal of Information Science
Event Recognition on News Stories and Semi-Automatic Population of an Ontology
WI '04 Proceedings of the 2004 IEEE/WIC/ACM International Conference on Web Intelligence
Text Mining: Predictive Methods for Analyzing Unstructured Information
Text Mining: Predictive Methods for Analyzing Unstructured Information
TextOntoEx: Automatic ontology construction from natural English text
Expert Systems with Applications: An International Journal
Hermes: a semantic web-based news decision support system
Proceedings of the 2008 ACM symposium on Applied computing
Construction of a Local Domain Ontology from News Stories
EPIA '09 Proceedings of the 14th Portuguese Conference on Artificial Intelligence: Progress in Artificial Intelligence
Enhancement of domain ontology construction using a crystallizing approach
Expert Systems with Applications: An International Journal
Analyzing entities and topics in news articles using statistical topic models
ISI'06 Proceedings of the 4th IEEE international conference on Intelligence and Security Informatics
A framework for ontology evolution in collaborative environments
ISWC'06 Proceedings of the 5th international conference on The Semantic Web
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Construction of business ontologies from news sources can produce a detailed representation of the chosen area, but the ontology may over time gather errors because information can become rapidly outdated. The two stage strategy described in this paper attempts to identify outdated relations in an ontology by affixing a confidence score to each relation and decaying the relation until a preset value where it is deleted or archived. The relation score is refreshed if the information is repeated in a news story. An evaluation demonstrates that over time erroneous information is removed and new information is added to the ontology.