FIT-IT Semantic Systems Program Line
Acquisition and Validation of Ontologies: An Adaptive Service
Architecture for Testing Semantic Hypotheses
Valuable knowledge that surrounds the workflows of business entities can be extracted automatically and represented as ontological structure. The methodology is built upon a cybernetic control system to automatically align extracted knowledge with business processes, external indicators, and individual expertise. The project’s adaptive services are particularly useful in volatile business environments, which require dynamic reconfiguration of business processes and a flexible allocation of resources. The AVALON project applies these methodologies and technologies in two different domains, trend scouting, and human resource development.
AVALON introduces a radically new generation of adaptive knowledge acquisition and management services that use feedback loops to semantically align extracted knowledge with business processes, external indicators, and individual expertise. Such adaptive services are particularly useful in volatile business environments, which require dynamic reconfiguration of business processes and a flexible composition of project teams. Considering the dynamically changing constraints and requirements of today’s economy, the goal-oriented assignment of personnel to business processes and the planning of vocational training are crucial. As a leading project in this area, AVALON demonstrates the potential of adaptive semantic technologies for optimizing business processes and allocating resources, and for dynamically assigning employees to business processes based on their competencies.
As outlined above, AVALON assumes that valuable knowledge surrounds the workflow of today’s business entities, which can be extracted and formally represented using ontologies. Coupling dynamic questionnaires with the automated creation and validation of ontologies, AVALON will substantially reduce manual efforts required to build and maintain comprehensive and topical knowledge bases. The underlying methodology represents a cybernetic control system that monitors real-world variables and, according to an internal knowledge base, recommends a particular action. If the decision-maker accepts the system’s recommendation, his or her action affects the real world. AVALON measures this change and immediately triggers an update of the knowledge base.
Semantic hypotheses relate the concepts embedded in this knowledge base to business processes and real-world indicators. To test these hypotheses, AVALON (i) automatically extracts knowledge from heterogeneous, unstructured information sources, (ii) discovers semantic associations within the knowledge base, and (iii) validates the knowledge on real-world indicators. The ontology-supported testing of semantic hypotheses will help create and manage ontologies, accelerate knowledge discovery, reveal trends, and increase the credibility of the continuously evolving knowledge base.
January 2006 – December 2007
- Graz University of Technology,
Knowledge Management Institute
- Vienna University of Economics and Business,
Department of Information and Process Management
- isn gmbh
- m2n gmbh