Tech Reports
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
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.
Future Internet
KnowledgeManagementMultimedia &
Information SystemsNarrative
HypermediaNew Media SystemsSemantic Web &
Knowledge ServicesSocial Software
Social Software is...
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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