Beyond Boolean Matrix Decompositions: Toward Factor Analysis and Dimensionality Reduction of Ordinal Data
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15310%2F13%3A33147956" target="_blank" >RIV/61989592:15310/13:33147956 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1109/ICDM.2013.127" target="_blank" >http://dx.doi.org/10.1109/ICDM.2013.127</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ICDM.2013.127" target="_blank" >10.1109/ICDM.2013.127</a>
Alternative languages
Result language
angličtina
Original language name
Beyond Boolean Matrix Decompositions: Toward Factor Analysis and Dimensionality Reduction of Ordinal Data
Original language description
Boolean matrix factorization (BMF), or decomposition, received a considerable attention in data mining research, both for its direct usefulness in data analysis and its fundamental role in understanding Boolean data. In this paper, we argue that researchshould extend beyond the Boolean case toward more general type of data such as ordinal data. Technically, such extension amounts to replacement of the two-element Boolean algebra utilized in BMF by more general structures, which brings non-trivial challenges. We first present the problem formulation, survey the existing literature, and provide an illustrative example. Second, we present new theorems regarding decompositions of matrices with ordinal data. The theorems helps understand the geometry of decompositions and identify parts of input matrices which are good to focus on when computing factors. Third, we propose two algorithms based on these results along with an experimental evaluation. We conclude the paper with a discussion re
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
<a href="/en/project/GAP103%2F11%2F1456" target="_blank" >GAP103/11/1456: Foundations of Similarity-Based Data Processing</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2013
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of 2013 IEEE 13th International Conference on Data Mining
ISBN
978-0-7685-5108-2
ISSN
1550-4786
e-ISSN
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Number of pages
6
Pages from-to
961-966
Publisher name
IEEE Computer Society Press
Place of publication
Los Alamos
Event location
Dallas
Event date
Dec 7, 2013
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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