Adding background knowledge to formal concept analysis via attribute dependency formulas
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15310%2F08%3A00005465" target="_blank" >RIV/61989592:15310/08:00005465 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Adding background knowledge to formal concept analysis via attribute dependency formulas
Original language description
We present a way to add user's background knowledge to formal concept analysis. The type of background knowledge we deal with relates to relative importance of attributes in the input data. We introduce AD-formulas which represent this type of backgroundknowledge. The background knowledge serves as a constraint. The main aim is to make extraction of clusters from the input data more focused by taking into account the background knowledge. Particularly, only clusterswhich are compatible with the background knowledge are extracted from data. As a result, the number of extracted clusters becomes smaller, leaving out non-interesting clusters. We present illustrative examples and results on entailment of background knowledge such as efficient testing of entailment and a complete systems of deduction rules.
Czech name
Přidání znalosti ve formální konceptuální analýze pomocí formulí pro zavislosti atributu
Czech description
Článek popisuje novou metodu, která umožňuje přidání znalosti ve formální konceptuální analýze pomoci formulí, popisujících závislosti atributu.
Classification
Type
D - Article in proceedings
CEP classification
BD - Information theory
OECD FORD branch
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Result continuities
Project
<a href="/en/project/1ET101370417" target="_blank" >1ET101370417: Hierarchical analysis of complex data</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2008
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of 23rd Annual ACM Symposium on Applied Computing
ISBN
978-1-59593-753-7
ISSN
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e-ISSN
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Number of pages
6
Pages from-to
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Publisher name
Association for Computing Machinery
Place of publication
New York, USA
Event location
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Event date
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Type of event by nationality
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UT code for WoS article
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