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Tech Report kmi-01-12 Abstract


Integration of Information Extraction with an Ontology
Techreport ID: kmi-01-12
Date: 2001
Author(s): Maria Vargas-Vera, John Domingue, Yannis Kalfoglou, Enrico Motta and Simon Buckingham Shum
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This paper describes the integration of an ontology with an information extraction (IE) tool. Our main goal is extract knowledge from text to populate the ontology, and so alleviate the problem of ontology maintenance. The IE tool extracts information using partial parsing and machine learning techniques. Our domain of study is ``KMi Planet'', a Web-based news server that helps to communicate relevant information between members in our institute. Currently our system finds instances of classes or subclasses. Although in the future we expect to create new classes and subclasses from new concepts appearing in text.
 
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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.