Decomposition-by-normalization (DBN): Leveraging approximate functional dependencies for efficient tensor decomposition

Mijung Kim, Kasim Candan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Scopus citations

Abstract

For many multi-dimensional data applications, tensor operations as well as relational operations need to be supported throughout the data lifecycle. Although tensor decomposition is shown to be effective for multi-dimensional data analysis, the cost of tensor decomposition is often very high. We propose a novel decomposition-by-normalization scheme that first normalizes the given relation into smaller tensors based on the functional dependencies of the relation and then performs the decomposition using these smaller tensors. The decomposition and recombination steps of the decomposition-by- normalization scheme fit naturally in settings with multiple cores. This leads to a highly efficient, effective, and parallelized decomposition-by-normalization algorithm for both dense and sparse tensors. Experiments confirm the efficiency and effectiveness of the proposed decomposition-by-normalization scheme compared to the conventional nonnegative CP decomposition approach.

Original languageEnglish (US)
Title of host publicationCIKM 2012 - Proceedings of the 21st ACM International Conference on Information and Knowledge Management
Pages355-364
Number of pages10
DOIs
StatePublished - Dec 19 2012
Event21st ACM International Conference on Information and Knowledge Management, CIKM 2012 - Maui, HI, United States
Duration: Oct 29 2012Nov 2 2012

Publication series

NameACM International Conference Proceeding Series

Other

Other21st ACM International Conference on Information and Knowledge Management, CIKM 2012
CountryUnited States
CityMaui, HI
Period10/29/1211/2/12

Keywords

  • tensor decomposition
  • tensor-based relational data model

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

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