Tech Reports
Tech Report kmi-08-04 Abstract
Evolva: Towards Automatic Ontology Evolution
Techreport ID: kmi-08-04
Date: 2008
Author(s): Fouad Zablith
Ontologies form the core of Semantic Web systems, and as such, they need to evolve to meet the changing needs of the system and its users. Information is exponentially increasing in organizations' intranets as well as on the web, especially with the increased popularity of tools facilitating content generation such as wikis, blogs and social software. In such dynamic environments, evolving ontologies should be agile, i.e. with the least knowledge experts' input, for reflecting fast changes occurring in repositories, and keeping Semantic Web systems up-to-date. Most of current ontology evolution frameworks mainly rely on user input throughout their evolution process. We propose Evolva, an ontology evolution framework, aiming to substantially reduce or even eliminate user input through exploiting various background knowledge sources. Background knowledge exists in various forms including lexical databases, web pages and Semantic Web ontologies. Evolva has five main components: information discovery, data validation, ontological changes, evolution validation and evolution management. We present in this report an overview of the current work on ontology evolution, followed by our ontology evolution approach and pilot study conducted so far, and we finally conclude with a discussion and our future directions.
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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