Selecting Important Concepts Using Weights

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15310%2F11%3A10225098" target="_blank" >RIV/61989592:15310/11:10225098 - 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

Selecting Important Concepts Using Weights

Popis výsledku v původním jazyce

We present an approach that enables one to select a reasonable small number of possibly important formal concepts from the set of all formal concepts of a given input data. The problem to select a small number of concepts appears in applications of formal concept analysis when the number of all formal concepts of the input data is large. Namely, a user often asks for a list of "important concepts" in such case. In the present approach, attributes of the input data are assigned weights from which valuesof formal concepts are determined. Formal concepts with larger values are considered more important. The attribute weights are supposed to be set by the users. The approach is a continuation of our previous approaches that utilize background knowledge, i.e. additional knowledge of a user, to select parts of concept lattices. In addition to the approach, we present illustrative examples.

Název v anglickém jazyce

Selecting Important Concepts Using Weights

Popis výsledku anglicky

We present an approach that enables one to select a reasonable small number of possibly important formal concepts from the set of all formal concepts of a given input data. The problem to select a small number of concepts appears in applications of formal concept analysis when the number of all formal concepts of the input data is large. Namely, a user often asks for a list of "important concepts" in such case. In the present approach, attributes of the input data are assigned weights from which valuesof formal concepts are determined. Formal concepts with larger values are considered more important. The attribute weights are supposed to be set by the users. The approach is a continuation of our previous approaches that utilize background knowledge, i.e. additional knowledge of a user, to select parts of concept lattices. In addition to the approach, we present illustrative examples.

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

<a href="/cs/project/GAP103%2F10%2F1056" target="_blank" >GAP103/10/1056: Konceptuální zpracování nejistých a rozsáhlých dat a znalostí</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>Z - Vyzkumny zamer (s odkazem do CEZ)

Rok uplatnění

2011

Kód důvěrnosti údajů

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

Název periodika

Lecture Notes in Computer Science

ISSN

0302-9743

e-ISSN

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Svazek periodika

6628

Číslo periodika v rámci svazku

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Stát vydavatele periodika

DE - Spolková republika Německo

Počet stran výsledku

16

Strana od-do

65-80

Kód UT WoS článku

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EID výsledku v databázi Scopus

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