Formal Concept Analysis with Attribute Priorities

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15310%2F09%3A00010944" target="_blank" >RIV/61989592:15310/09:00010944 - 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
Formal Concept Analysis with Attribute Priorities
Original language description
Formal concept analysis has recently been applied to data analysis, visualization, and knowledge extraction in various fields. Central to formal concept analysis is the notion of a formal concept which is a particular cluster in data. This chapter presents an extension of a basic setting of formal concept analysis. It allows a user to enter, along with the input data, his priorities regarding relative importance of attributes. Adding attribute priorities results in extraction of only those clusters in data which are compatible with the attribute priorities. The main effect is that the user is supplied with a smaller number of more relevant clusters and is thus not overwhelmed by a possibly large number of all formal concepts which logically exist in data. In this overview chapter, we present the approach and illustrative examples from marketing.
Czech name
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Czech description
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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)

Publication year
2009
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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