Background Knowledge in Formal Concept Analysis: Constraints via Closure Operators.

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15310%2F10%3A10216466" target="_blank" >RIV/61989592:15310/10:10216466 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Background Knowledge in Formal Concept Analysis: Constraints via Closure Operators.
Original language description
The aim of this short paper is to present a general method of using background knowledge to impose constraints in conceptual clustering of object-attribute relational data. The proposed method uses the background knowledge to extract only particular clusters from the input data -- those which are compatible with the background knowledge and thus satisfy the constraint. As a result, the method allows for extracting less clusters in a shorter time which are in addition more interesting. The paper presentsthe idea of constraints formalized by means of closure operators and introduces such constraints to formal concept analysis. Among the bene ts of the presented approach are its versatility (the approach covers several examples studied before, e.g. extraction of closed frequent itemsets in generation of non-redundant association rules) and computational efficiency. Due to scope limitations, we present the main ideas only. Details will be available in a full version of this paper.
Czech name
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Czech description
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Publication year
2010
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proceedings of the 25th Symposium On Applied Computing
ISBN
978-1-60558-638-0
ISSN
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e-ISSN
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Number of pages
2
Pages from-to
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Publisher name
ACM Press
Place of publication
New York
Event location
Sierre, Švýcarsko
Event date
Mar 22, 2010
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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