Deutsch
 
Hilfe Datenschutzhinweis Impressum
  DetailsucheBrowse

Datensatz

DATENSATZ AKTIONENEXPORT
 
 
DownloadE-Mail
 Lokale TagsFreigabegeschichteDetailsÜbersicht
  Sparse Boolean Matrix Factorizations

Miettinen, P. (2010). Sparse Boolean Matrix Factorizations. In G. I. Webb, B. Liu, C. Zhang, D. Gunopulos, & X. Wu (Eds.), 10th IEEE International Conference on Data Mining (pp. 935-940). Los Alamitos, CA: IEEE Computer Society.

Item is

 

einblenden: alle ausblenden: alle

Basisdaten

einblenden: ausblenden:
Datensatz-Permalink: https://hdl.handle.net/11858/00-001M-0000-000F-1532-2 Versions-Permalink: https://hdl.handle.net/11858/00-001M-0000-0024-3A6C-6
Genre: Konferenzbeitrag
Latex : Sparse {B}oolean Matrix Factorizations

Externe Referenzen

einblenden:

Urheber

einblenden:
ausblenden:
 Urheber:
Miettinen, Pauli1, Autor           
Affiliations:
1Databases and Information Systems, MPI for Informatics, Max Planck Society, ou_24018              

Inhalt

einblenden:
ausblenden:
Schlagwörter: -
 Zusammenfassung: Matrix factorizations are commonly used methods in data mining. When the input data is Boolean, replacing the standard matrix multiplication with Boolean matrix multiplication can yield more intuitive results. Unfortunately, finding a good Boolean decomposition is known to be computationally hard, with even many sub-problems being hard to approximate. Many real-world data sets are sparse, and it is often required that also the factor matrices are sparse. This requirement has motivated many new matrix decomposition methods and many modifications of the existing methods. This paper studies how Boolean matrix factorizations behave with sparse data: can we assume some sparsity on the factor matrices, and does the sparsity help with the computationally hard problems. The answer to these problems is shown to be positive.

Details

einblenden:
ausblenden:
Sprache(n): eng - English
 Datum: 2010
 Publikationsstatus: Erschienen
 Seiten: -
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: -
 Identifikatoren: eDoc: 536399
DOI: 10.1109/ICDM.2010.93
URI: http://dx.doi.org/10.1109/ICDM.2010.93
Anderer: Local-ID: C1256DBF005F876D-2D9263E452E2F763C125781D0056B88A-miettinen10sparse
 Art des Abschluß: -

Veranstaltung

einblenden:
ausblenden:
Titel: 10th IEEE International Conference on Data Mining
Veranstaltungsort: Sydeny, Australia
Start-/Enddatum: 2010-12-14 - 2010-12-17

Entscheidung

einblenden:

Projektinformation

einblenden:

Quelle 1

einblenden:
ausblenden:
Titel: 10th IEEE International Conference on Data Mining
  Kurztitel : ICDM 2010
Genre der Quelle: Konferenzband
 Urheber:
Webb, Geoffrey I.1, Herausgeber
Liu, Bing1, Herausgeber
Zhang, Chengqi1, Herausgeber
Gunopulos, Dimitrios2, Herausgeber           
Wu, Xindong1, Herausgeber
Affiliations:
1 External Organizations, ou_persistent22            
2 Algorithms and Complexity, MPI for Informatics, Max Planck Society, ou_24019            
Ort, Verlag, Ausgabe: Los Alamitos, CA : IEEE Computer Society
Seiten: - Band / Heft: - Artikelnummer: - Start- / Endseite: 935 - 940 Identifikator: ISBN: 978-0-7695-4256-0