Publikationen

Hier finden Sie von Know-Center MitarbeiterInnen verfasste wissenschaftliche Publikationen

2007

Ghidini C., Pammer-Schindler Viktoria, Scheir Peter, Lindstaedt Stefanie , Serafini L.

APOSDLE: learn@work with semantic web technology

Proceedings of I-MEDIA 2007 and I-SEMANTICS 2007, Graz, Austria, September 5-7, 2007, 2007

Konferenz
The EU project APOSDLE focuses on work-integrated learning. Among the severalchallenges of the project, a crucial role is played by the system’s ability to start from the context ofthe immediate work of a user, establish her missing competencies and learning needs and suggeston-the-fly and appropriate learning stimuli. These learning stimuli are created from a variety ofresources (documents, videos, expert profiles, and so on) already stored in the workplace andmay be in the form of learning material or suggestions to contact experts and / or colleagues.To address this challenge requires the capability of building a system which is able find, choose,share, and combine a variety of knowledge, evolving content and resources in an automatic andeffective manner. The implementation of this capability requires technology which goes beyondtraditional query-answering and keyword based search engines, and Semantic Web technologywas chosen by the consortium as the most appropriate technology to make information search anddata integration more efficient. The aim of this paper is to give an overview of the broad spectrumof Semantic Web technologies that are needed for a complex application like APOSDLE, and thechallenges for the Semantic Web community that have appeared along the way.
2007

Scheir Peter, Ghidini C., Lindstaedt Stefanie

Improving Search on the Semantic Desktop using Associative Retrieval Techniques

Proceedings of I-MEDIA 2007 and I-SEMANTICS 2007, Graz, Austria, September 5-7, 2007, 2007

Konferenz
While it is agreed that semantic enrichment of resources would lead tobetter search results, at present the low coverage of resources on the web with semanticinformation presents a major hurdle in realizing the vision of search on the SemanticWeb. To address this problem we investigate how to improve retrieval performancein a setting where resources are sparsely annotated with semantic information. Wesuggest employing techniques from associative information retrieval to find relevantmaterial, which was not originally annotated with the concepts used in a query. Wepresent an associative retrieval system for the Semantic Desktop and show how the useof associative retrieval increased retrieval performance.
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