Image Processing in Boolean Matrix Factorization
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15310%2F25%3A73633775" target="_blank" >RIV/61989592:15310/25:73633775 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/chapter/10.1007/978-3-032-03364-2_18" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-032-03364-2_18</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-032-03364-2_18" target="_blank" >10.1007/978-3-032-03364-2_18</a>
Alternative languages
Result language
angličtina
Original language name
Image Processing in Boolean Matrix Factorization
Original language description
Boolean matrix factorization (BMF) is a data mining method that decomposes a binary matrix into the Boolean product of two smaller matrices, revealing hidden patterns in that matrix. Traditional BMF algorithms overlook visual aspects, limiting their ability to identify natural factors. This paper explores the use of image processing methods to enhance BMF. We propose treating Boolean matrices as black-and-white images and applying methods such as analysis connected component, SLIC segmentation, Quad tree, spatial filtering, and morphological operations. Experiments on real and synthetic datasets demonstrate that these methods highlight relevant structures in data and improves factor computation.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
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
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Lecture Notes in Computer Science
ISBN
978-3-032-03363-5
ISSN
0302-9743
e-ISSN
1611-3349
Number of pages
14
Pages from-to
281-294
Publisher name
Springer Science and Business Media Deutschland GmbH
Place of publication
Heidelberg
Event location
Cluj-Napoca
Event date
Sep 8, 2025
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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