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Tech Report kmi-03-10 Abstract


Event Recognition using Information Extraction Techniques
Techreport ID: kmi-03-10
Date: 2003
Author(s): Maria Vargas-Vera, David Celjuska
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This paper describes a system which recognizes events on stories. Our system classifies stories and populates a KMi Planet ontology with new instances of classes defined in it. Currently, the system recognizes events which can be classified as belonging to a single category and it also recognizes overlapping events (more than one event is recognized in the story). In each case, the system provides a confidence value associated to the suggested classification. In our event recognition system we use Information Extraction and Machine Learning technologies. We have tested this system using an archive of stories describing the academic life of our institution (these stories describe events such as an project award, publications, visits, etc.)
 
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Knowledge Management is...


Knowledge Management
Creating learning organisations hinges on managing knowledge at many levels. Knowledge can be provided by individuals or it can be created as a collective effort of a group working together towards a common goal, it can be situated as "war stories" or it can be generalised as guidelines, it can be described informally as comments in a natural language, pictures and technical drawings or it can be formalised as mathematical formulae and rules, it can be expressed explicitly or it can be tacit, embedded in the work product. The recipient of knowledge - the learner - can be an individual or a work group, professionals, university students, schoolchildren or informal communities of interest.
Our aim is to capture, analyse and organise knowledge, regardless of its origin and form and make it available to the learner when needed presented with the necessary context and in a form supporting the learning processes.