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Tech Report kmi-04-11 Abstract


Semi-Automatic Construction of Ontologies from Text
Techreport ID: kmi-04-11
Date: 2004
Author(s): David Celjuska
Supervisors: Maria Vargas-Vera, Jan Paralic
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The Master's Thesis deals with semi-automatic construction of ontologies from text. While the core of the thesis was to develop an integrated system for ontology population with instances extracted from text, it also discusses and analyzes two major existing approaches in this area. The system is based on supervised learning and therefore learns extraction rules from annotated text and then applies those rules on new documents for the extraction. The important part of the entire cycle of ontology population is a user who accepts, rejects or modifies new extractions and suggested instances to be populated. An analysis of the possibility of automatically creation of new classes is discussed in turn.
 
KMi Publications Event | SSSW 2013, The 10th Summer School on Ontology Engineering and the Semantic Web Journal | 25 years of knowledge acquisition
 

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.