Hier finden Sie von Know-Center MitarbeiterInnen verfasste wissenschaftliche Publikationen


Lux Mathias, Scheir Peter, Lindstaedt Stefanie , Granitzer Michael

Special Track on Advanced Semantic Technologies-Introduction

International Conference on Knowledge Management, 2006


Scheir Peter, Granitzer Michael, Lindstaedt Stefanie , Hofmair P.

The OntologyMapper plug-in: Supporting Semantic Annotation of Text-Documents by Classification

Semantic Systems From Vision to Applications - Proceedings of the SEMANTICS 2006, Vienna, Austria, November 28-30, 2006, Österreichische Computer Gesellschaft, Wien, 2006

In this contribution we present a tool for annotating documents, which are used for workintegratedlearning, with concepts from an ontology. To allow for annotating directly whilecreating or editing an ontology, the tool was realized as a plug-in for the ontology editor Protégé.Annotating documents with semantic metadata is a laborious task, most of the time knowledgerepresentations are created independently from the resources that should be annotated andadditionally in most work environments a high number of documents exist. To increase theefficiency of the person annotating, in our tool the process of assigning concepts to text-documentsis supported by automatic text-classification.

Pammer-Schindler Viktoria, Scheir Peter, Lindstaedt Stefanie

Ontology Coverage Check: Support for Evaluation in Ontology Engineering

Proceedings of FOMI 2006 - 2nd Workshop on Formal Ontologies Meet Industry, Trento, Italy, December 14-15, 2006, 2006

Support for the process of ontology engineering is needed in order to reduce theeffort still necessary to build an ontology. Some can be given by facilitated evaluationof the ontology under development. To that purpose we present an automated methodthat supports data driven ontology evaluation by checking to what extent the conceptsand axioms of the ontology under evaluation are covered by a given set of individuals(data).We applied the here presented ontology coverage check (OCC) to various ontologiesand will report on the results. The results highlight not only the potential of OCCbut also some characteristics of ontologies currently available to the public.

Scheir Peter

Associative retrieval of resources for work-integrated learning: Integrating domain knowledge with content-based similarities

in: Maillet, K., Klamma, R. (Ed.), Proceedings of the 1st Doctoral Consortium in Technology Enhanced Learning, Crete, Greece, October 2, 2006, Aachen, 2006


Scheir Peter, Lindstaedt Stefanie

A network model approach to document retrieval taking into account domain knowledge

In Martin Schaaf and Klaus-Dieter Althoff (Ed.), Proceedings LWA 2006 - Lernen - Wissensentdeckung - Adaptivität, Hildesheim, Germany, October 9-11, 2006, Universität Hildesheim, Hildesheim, 2006

We preset a network model for context-based retrievalallowing for integrating domain knowledgeinto document retrieval. Based on thepremise that the results provided by a networkmodel employing spreading activation are equivalentto the results of a vector space model, wecreate a network representation of a documentcollection for retrieval. We extended this well exploredapproach by blending it with techniquesfrom knowledge representation. This leaves uswith a network model for finding similarities in adocument collection by content-based as well asknowledge-based similarities.

Ulbrich Armin, Lindstaedt Stefanie , Scheir Peter, Goertz M.

A Context-Model for Supporting Work-Integrated Learning

European Conference on Technology Enhanced Learning, Innovative Approaches for Learning and Knowledge Sharing , Springer, Berlin, 2006

This contribution introduces the so-called Workplace Learning Contextas essential conceptualisation supporting self-directed learning experiencesdirectly at the workplace. The Workplace Learning Context is to be analysedand exploited for retrieving ‘learning’ material that best-possibly matches witha knowledge worker’s current learning needs. In doing so, several different‘flavours’ of work-integrated learning can be realised including task learning,competency-gap based support and domain-related support. The WorkplaceLearning Context Model, which is also outlined in this contribution, forms thetechnical representation of the Workplace Learning Context.
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