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
Multimedia and Information Systems is...

We focus on content-based information retrieval over a wide range of data spanning form unstructured text and unlabelled images over spoken documents and music to videos. This encompasses the modelling of human perception of relevance and similarity, the learning from user actions and the up-to-date presentation of information. Currently we are building a research version of an integrated multimedia information retrieval system MIR to be used as a research prototype. We aim for a system that understands the user's information need and successfully links it to the appropriate information sources, be it a report or a TV news clip. This work is guided by the vision that an automated knowledge extraction system ultimately empowers people making efficient use of information sources without the burden of filing data into specialised databases.
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