Interaktivní dolování dat nad hierarchickými daty

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F07%3APU73631" target="_blank" >RIV/00216305:26230/07:PU73631 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Interactive Mining on Hierarchical Data

Popis výsledku v původním jazyce

In this paper, we propose a framework for interactive, iterative, and intuitive mining of multilevel association, characterization and classification rules on data organized in multi-level conceptual hierarchies. This framework is called OLAM SE (Self Explaining On-Line Analytical Mining) and it is proposed as an extension of OLAP or as an alternative to Han's OLAM. OLAM processes data stored in data cubes structure of which is based on a given conceptual hierarchy. OLAM SE determines minimum support value from user defined cover value of data with usage of entropy coding principle. It also automatically determines the maximum threshold to avoid explaining knowledge that is obvious and so potentially uninteresting. Major part of data is thus describedby frequent patterns. The presentation of results is inspired by UML diagram notation. It contains a graph nodes of which are frequent data sets represented as packages including sub packages - data classes or items. Edges represent relat

Název v anglickém jazyce

Interactive Mining on Hierarchical Data

Popis výsledku anglicky

In this paper, we propose a framework for interactive, iterative, and intuitive mining of multilevel association, characterization and classification rules on data organized in multi-level conceptual hierarchies. This framework is called OLAM SE (Self Explaining On-Line Analytical Mining) and it is proposed as an extension of OLAP or as an alternative to Han's OLAM. OLAM processes data stored in data cubes structure of which is based on a given conceptual hierarchy. OLAM SE determines minimum support value from user defined cover value of data with usage of entropy coding principle. It also automatically determines the maximum threshold to avoid explaining knowledge that is obvious and so potentially uninteresting. Major part of data is thus describedby frequent patterns. The presentation of results is inspired by UML diagram notation. It contains a graph nodes of which are frequent data sets represented as packages including sub packages - data classes or items. Edges represent relat

Druh

D - Stať ve sborníku

CEP obor

BC - Teorie a systémy řízení

OECD FORD obor

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Projekt

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Návaznosti

Z - Vyzkumny zamer (s odkazem do CEZ)

Rok uplatnění

2007

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings of the 13th Conference STUDENT EEICT 2007 Volume 4

ISBN

978-80-214-3410-3

ISSN

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e-ISSN

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Počet stran výsledku

5

Strana od-do

410-414

Název nakladatele

Brno University of Technology

Místo vydání

Brno

Místo konání akce

Brno

Datum konání akce

26. 4. 2007

Typ akce podle státní příslušnosti

CST - Celostátní akce

Kód UT WoS článku

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