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− | |Abstract=Ontology reuse saves costs and improves interoperability between ontologies. Knowing which ontology to reuse is difficult without having a quality assessment. We employ user ratings to determine the user-perceived quality of ontologies. The combination of an Open | + | |Abstract=Ontology reuse saves costs and improves interoperability between ontologies. Knowing which ontology to reuse is difficult without having a quality assessment. We employ user ratings to determine the user-perceived quality of ontologies. The combination of an Open Rating System (ORS), user ratings, and information on trust between users, allow us to compute a personalized ranking of ontologies. In this paper, we present our extension, the Topic-Specific Trust Open Rating System (TS-ORS). To overcome the limitations of the ORS, the TS-ORS features topic-specific trust and multi-faceted ratings. In a user study, we show that having user ratings and result ranking based on a TS-ORS significantly facilitates ontology assessment and selection for the end user. |
|ISBN=978-3-642-16437-8 | |ISBN=978-3-642-16437-8 | ||
|Projekt=Active | |Projekt=Active | ||
|Forschungsgruppe=Wissensmanagement | |Forschungsgruppe=Wissensmanagement | ||
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Version vom 22. September 2010, 08:17 Uhr
Extending Open Rating Systems for Ontology Ranking and Reuse
Extending Open Rating Systems for Ontology Ranking and Reuse
Published: 2010
Oktober
Herausgeber: Philipp Cimiano, H. Sofia Pinto
Buchtitel: Knowledge Engineering: Practice and Patterns, 17th International Conference, EKAW 2010, Lisbon, Portugal, October 11-15, 2010, Proceedings
Nummer: 6317
Reihe: Lecture Notes in Computer Science
Verlag: Springer
Referierte Veröffentlichung
Note: to appear
BibTeX
Kurzfassung
Ontology reuse saves costs and improves interoperability between ontologies. Knowing which ontology to reuse is difficult without having a quality assessment. We employ user ratings to determine the user-perceived quality of ontologies. The combination of an Open Rating System (ORS), user ratings, and information on trust between users, allow us to compute a personalized ranking of ontologies. In this paper, we present our extension, the Topic-Specific Trust Open Rating System (TS-ORS). To overcome the limitations of the ORS, the TS-ORS features topic-specific trust and multi-faceted ratings. In a user study, we show that having user ratings and result ranking based on a TS-ORS significantly facilitates ontology assessment and selection for the end user.
ISBN: 978-3-642-16437-8