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D3.2.2 Usage-driven Change Discovery: Evaluation

Published: 2006 Januar
Type: SEKT Deliverable
Nummer: 3.2.2Der Datenwert „.2.2“ kann einem Attribut des Datentyps Zahl nicht zugeordnet werden sondern bspw. der Datenwert „3“.
Institution: University of Karlsruhe


The world is constantly changing, and so does required and available knowledge, e.g. stored in Digital Libraries. Knowledge workers heavily rely on the availability and accessibility of knowledge contained in such libraries. The sheer mass of knowledge available today, however, requires sophisticated support for searching and, often considered as equally important, personalization.

In SEKT we address these challenges by using ontologies. Ontologies by nature make implicit knowledge explicit, they describe relevant parts of the world and make them machine understandable and processable. To be effective, ontologies need to change possibly as fast as the parts of the world they describe.

Change discovery aims at generating implicit requirements by inducing ontology changes from existing data. We here focus on {em usage-driven} change discovery. Usage data is a very valuable source of contextual information, based on which the ontology can be modified in order to reflect changes in the real world,

In a precedent deliverable we have presented a framework for usage-driven ontology evolution along with a set of methods for change discovery. In this deliverable we evaluate this framework by applying it to actual use cases from the BT DL case study. The use cases include (1) usage-based pruning of a generic ontology to obtain a personalized ontology, and (2) extending an existing ontology with personalized extensions obtained via Ontology Learning techniques. The evaluation results show the usefulness of applying usage data for the task of ontology evolution.

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Ontologiebasierte Wissensmanagementsysteme