Tech Reports
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
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.
Future Internet
KnowledgeManagementMultimedia &
Information SystemsNarrative
HypermediaNew Media SystemsSemantic Web &
Knowledge ServicesSocial Software
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Interacting with other people not only forms the core of human social and psychological experience, but also lies at the centre of what makes the internet such a rich, powerful and exciting collection of knowledge media. We are especially interested in what happens when such interactions take place on a very large scale -- not only because we work regularly with tens of thousands of distance learners at the Open University, but also because it is evident that being part of a crowd in real life possesses a certain 'buzz' of its own, and poses a natural challenge. Different nuances emerge in different user contexts, so we choose to investigate the contexts of work, learning and play to better understand the trade-offs involved in designing effective large-scale social software for multiple purposes.
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