Data Reduction for Boolean Matrix Factorization Algorithms Based on Formal Concept Analysis

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15310%2F18%3A73588504" target="_blank" >RIV/61989592:15310/18:73588504 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.sciencedirect.com/science/article/pii/S0950705118302594" target="_blank" >https://www.sciencedirect.com/science/article/pii/S0950705118302594</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.knosys.2018.05.035" target="_blank" >10.1016/j.knosys.2018.05.035</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Data Reduction for Boolean Matrix Factorization Algorithms Based on Formal Concept Analysis

Popis výsledku v původním jazyce

Data size reduction is an important step in many data mining techniques. We present a novel approach based on formal concept analysis to data reduction tailored for Boolean matrix factorization methods. A general aim of these methods is to find factors that exactly or approximately explain data. The presented approach is able to significantly reduce the size of data by choosing a representative set of rows, and preserve (with a little loss) factors behind the data, i.e. it only slightly affects a quality of the factors produced by Boolean matrix factorization algorithms.

Název v anglickém jazyce

Data Reduction for Boolean Matrix Factorization Algorithms Based on Formal Concept Analysis

Popis výsledku anglicky

Data size reduction is an important step in many data mining techniques. We present a novel approach based on formal concept analysis to data reduction tailored for Boolean matrix factorization methods. A general aim of these methods is to find factors that exactly or approximately explain data. The presented approach is able to significantly reduce the size of data by choosing a representative set of rows, and preserve (with a little loss) factors behind the data, i.e. it only slightly affects a quality of the factors produced by Boolean matrix factorization algorithms.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

<a href="/cs/project/GA15-17899S" target="_blank" >GA15-17899S: Rozklady matic s booleovskými a ordinálními daty: teorie a algoritmy</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2018

Kód důvěrnosti údajů

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

Název periodika

KNOWLEDGE-BASED SYSTEMS

ISSN

0950-7051

e-ISSN

—

Svazek periodika

158

Číslo periodika v rámci svazku

OCT

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

6

Strana od-do

75-80

Kód UT WoS článku

000440529200007

EID výsledku v databázi Scopus

2-s2.0-85053035664