The 8M Algorithm from Today's Perspective
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15310%2F21%3A73607787" target="_blank" >RIV/61989592:15310/21:73607787 - isvavai.cz</a>
Result on the web
<a href="https://obd.upol.cz/id_publ/333187673" target="_blank" >https://obd.upol.cz/id_publ/333187673</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1145/3428078" target="_blank" >10.1145/3428078</a>
Alternative languages
Result language
angličtina
Original language name
The 8M Algorithm from Today's Perspective
Original language description
We provide a detailed analysis and a first complete description of 8M-an old but virtually unknown algorithm for Boolean matrix factorization. Even though the algorithm uses a rather limited insight into the factorization problem from today's perspective, we demonstrate that its performance is reasonably good compared to the currently available algorithms. Our analysis reveals that this is due to certain concepts employed by 8M that are not exploited by the current algorithms. We discuss the prospect of these concepts, utilize them to improve two well-known current factorization algorithms, and, furthermore, propose an improvement of 8M itself, which significantly enhances the performance of the original 8M. Our findings are illustrated by experimental evaluation.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
ACM Transactions on Knowledge Discovery from Data
ISSN
1556-4681
e-ISSN
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Volume of the periodical
15
Issue of the periodical within the volume
2
Country of publishing house
US - UNITED STATES
Number of pages
22
Pages from-to
"22-1"-"22-22"
UT code for WoS article
000639049700009
EID of the result in the Scopus database
2-s2.0-85103942655