Approximate tensor decomposition within a tensor-relational algebraic framework

Mijung Kim, Kasim Candan

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

12 Scopus citations

Abstract

In this paper, we first introduce a tensor-based relational data model and define algebraic operations on this model. We note that, while in traditional relational algebraic systems the join operation tends to be the costliest operation of all, in the tensor-relational framework presented here, tensor decomposition becomes the computationally costliest operation. Therefore, we consider optimization of tensor decomposition operations within a relational algebraic framework. This leads to a highly efficient, effective, and easy-to-parallelize join-by-decomposition approach and a corresponding KL-divergence based optimization strategy. Experimental results provide evidence that minimizing KL-divergence within the proposed join-by-decomposition helps approximate the conventional join-then-decompose scheme well, without the associated time and space costs.

Original languageEnglish (US)
Title of host publicationCIKM'11 - Proceedings of the 2011 ACM International Conference on Information and Knowledge Management
Pages1737-1742
Number of pages6
DOIs
StatePublished - Dec 13 2011
Event20th ACM Conference on Information and Knowledge Management, CIKM'11 - Glasgow, United Kingdom
Duration: Oct 24 2011Oct 28 2011

Publication series

NameInternational Conference on Information and Knowledge Management, Proceedings

Other

Other20th ACM Conference on Information and Knowledge Management, CIKM'11
CountryUnited Kingdom
CityGlasgow
Period10/24/1110/28/11

Keywords

  • approximate tensor decomposition
  • tensor relational algebra
  • tensor-based relational model

ASJC Scopus subject areas

  • Decision Sciences(all)
  • Business, Management and Accounting(all)

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  • Cite this

    Kim, M., & Candan, K. (2011). Approximate tensor decomposition within a tensor-relational algebraic framework. In CIKM'11 - Proceedings of the 2011 ACM International Conference on Information and Knowledge Management (pp. 1737-1742). (International Conference on Information and Knowledge Management, Proceedings). https://doi.org/10.1145/2063576.2063827