Model order selection for approximate Boolean matrix factorization problem

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15310%2F21%3A73607834" target="_blank" >RIV/61989592:15310/21:73607834 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.sciencedirect.com/science/article/pii/S0950705121004469" target="_blank" >https://www.sciencedirect.com/science/article/pii/S0950705121004469</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.knosys.2021.107184" target="_blank" >10.1016/j.knosys.2021.107184</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Model order selection for approximate Boolean matrix factorization problem

Popis výsledku v původním jazyce

A key step in applying Boolean matrix factorization (BMF) is establishing the correct model order for the data, i.e., decide where the knowledge stops and the noise starts, or simply, decide the proper number of factors that describe the data well. There are two main approaches to BMF, namely, Discrete Basis Problem (DBP) and Approximation Factorization Problem (AFP). Although the model order selection technique for DBP exists, there is no technique tailored for AFP. We show that the number of factors for DBP cannot be used in AFP, and we present a novel way, reflecting the nature of AFP, how to establish the proper number of factors. Moreover, we show that the number of factors established for AFP is - from a knowledge-representation viewpoint - better than that for DBP.

Název v anglickém jazyce

Model order selection for approximate Boolean matrix factorization problem

Popis výsledku anglicky

A key step in applying Boolean matrix factorization (BMF) is establishing the correct model order for the data, i.e., decide where the knowledge stops and the noise starts, or simply, decide the proper number of factors that describe the data well. There are two main approaches to BMF, namely, Discrete Basis Problem (DBP) and Approximation Factorization Problem (AFP). Although the model order selection technique for DBP exists, there is no technique tailored for AFP. We show that the number of factors for DBP cannot be used in AFP, and we present a novel way, reflecting the nature of AFP, how to establish the proper number of factors. Moreover, we show that the number of factors established for AFP is - from a knowledge-representation viewpoint - better than that for DBP.

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

—

Návaznosti

S - Specificky vyzkum na vysokych skolach<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2021

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

1872-7409

Svazek periodika

227

Číslo periodika v rámci svazku

SEP

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

5

Strana od-do

"107184-1"-"107184-5"

Kód UT WoS článku

000679379400011

EID výsledku v databázi Scopus

2-s2.0-85120765649