An empirical study of automated dictionary construction for information extraction in three domains
Artificial Intelligence - Special volume on empirical methods
Learning to construct knowledge bases from the World Wide Web
Artificial Intelligence - Special issue on Intelligent internet systems
Constructing Biological Knowledge Bases by Extracting Information from Text Sources
Proceedings of the Seventh International Conference on Intelligent Systems for Molecular Biology
Construction of a Local Domain Ontology from News Stories
EPIA '09 Proceedings of the 14th Portuguese Conference on Artificial Intelligence: Progress in Artificial Intelligence
Semantic tracking in peer-to-peer topic maps management
DNIS'07 Proceedings of the 5th international conference on Databases in networked information systems
Semi-automatic financial events discovery based on lexico-semantic patterns
International Journal of Web Engineering and Technology
Construction and maintenance of a fuzzy temporal ontology from news stories
International Journal of Metadata, Semantics and Ontologies
Event recognition based on co-occurrence concept analysis
CLSW'12 Proceedings of the 13th Chinese conference on Chinese Lexical Semantics
Semantics-based information extraction for detecting economic events
Multimedia Tools and Applications
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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.)