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Improving Taxonomy Maintenance

Subtitle
Automated Splitting and Merging of Taxonomies
Abstract
In Case-Based Reasoning (CBR), taxonomies are often used to model similarities. For complex domains and tasks such taxonomies tend to increase in size making them hard to model and maintain. This especially holds true if a group of people is working on the same taxonomy simultaneously. In this paper, we propose a solution by dividing larger taxonomies into sub-taxonomies, which can be regarded as individual and independent taxonomies. Through compilation, they can be merged and put back into their original context.
Publication Type
ConferencePaper
Author
Flöter, Moritz 
•
Reuß, Pascal 
•
Ude, Johannes 
•
Althoff, Klaus-Dieter 
Editor
Leyer, Michael
Date Issued
2017
Faculty
Fachbereich 4 
Institute / Institution
Institut für Informatik 
Published in
LWDA 2017: Lernen, Wissen, Daten, Analysen 2017
Conference
Lernen, Wissen, Daten, Analysen, Rostock, 11.09.-13.09.2017
Publisher
CEUR-WS
Publisher Place
Aachen
Page Start
3
Page End
14
Series Name
CEUR Workshop Proceedings
Issue Number
1917
Link to the original publication
https://ceur-ws.org/Vol-1917/paper03.pdf
HilPub short link
https://hilpub.uni-hildesheim.de/handle/ubhi/10863
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