article

Computational complexity of queries based on itemsets

Author:

Nikolaj TattiAuthors Info & Claims

Information Processing Letters, Volume 98, Issue 5

Pages 183 - 187

Published: 15 June 2006 Publication History

Abstract

We investigate determining the exact bounds of the frequencies of conjunctions based on frequent sets. Our scenario is an important special case of some general probabilistic logic problems that are known to be intractable. We show that despite the limitations our problems are also intractable, namely, we show that checking whether the maximal consistent frequency of a query is larger than a given threshold is NP-complete and that evaluating the Maximum Entropy estimate of a query is PP-hard. We also prove that checking consistency is NP-complete.

References

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Cited By

Dalleiger SVreeken JZhang ARangwala H(2022)Discovering Significant Patterns under Sequential False Discovery ControlProceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining10.1145/3534678.3539398(263-272)Online publication date: 14-Aug-2022
https://dl.acm.org/doi/10.1145/3534678.3539398
Wu HNing YChakraborty PVreeken JTatti NRamakrishnan N(2018)Generating Realistic Synthetic Population DatasetsACM Transactions on Knowledge Discovery from Data10.1145/318238312:4(1-22)Online publication date: 16-Apr-2018
https://dl.acm.org/doi/10.1145/3182383
Wu HSun MMi PTatti NNorth CRamakrishnan N(2018)Interactive Discovery of Coordinated Relationship Chains with Maximum Entropy ModelsACM Transactions on Knowledge Discovery from Data10.1145/304701712:1(1-34)Online publication date: 31-Jan-2018
https://dl.acm.org/doi/10.1145/3047017
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Index Terms

Computational complexity of queries based on itemsets
1. Information systems
  1. Data management systems
    1. Database management system engines
      1. Database query processing
  2. Information systems applications
    1. Data mining
2. Theory of computation
  1. Computational complexity and cryptography
    1. Complexity classes
  2. Theory and algorithms for application domains
    1. Database theory
      1. Database query processing and optimization (theory)

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Published In

cover image Information Processing Letters

Information Processing Letters Volume 98, Issue 5

15 June 2006

59 pages

ISSN:0020-0190

Issue’s Table of Contents

Copyright © Elsevier B.V. © 2006.

Publisher

Elsevier North-Holland, Inc.

United States

Publication History

Published: 15 June 2006

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Cited By

Dalleiger SVreeken JZhang ARangwala H(2022)Discovering Significant Patterns under Sequential False Discovery ControlProceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining10.1145/3534678.3539398(263-272)Online publication date: 14-Aug-2022
https://dl.acm.org/doi/10.1145/3534678.3539398
Wu HNing YChakraborty PVreeken JTatti NRamakrishnan N(2018)Generating Realistic Synthetic Population DatasetsACM Transactions on Knowledge Discovery from Data10.1145/318238312:4(1-22)Online publication date: 16-Apr-2018
https://dl.acm.org/doi/10.1145/3182383
Wu HSun MMi PTatti NNorth CRamakrishnan N(2018)Interactive Discovery of Coordinated Relationship Chains with Maximum Entropy ModelsACM Transactions on Knowledge Discovery from Data10.1145/304701712:1(1-34)Online publication date: 31-Jan-2018
https://dl.acm.org/doi/10.1145/3047017
Wu HVreeken JTatti NRamakrishnan N(2018)Uncovering the plotData Mining and Knowledge Discovery10.1007/s10618-014-0370-128:5-6(1398-1428)Online publication date: 26-Dec-2018
https://dl.acm.org/doi/10.1007/s10618-014-0370-1
Tatti NVreeken J(2018)Comparing apples and orangesData Mining and Knowledge Discovery10.1007/s10618-012-0275-925:2(173-207)Online publication date: 26-Dec-2018
https://dl.acm.org/doi/10.1007/s10618-012-0275-9
Kalofolias JGalbrun EMiettinen P(2018)From sets of good redescriptions to good sets of redescriptionsKnowledge and Information Systems10.1007/s10115-017-1149-757:1(21-54)Online publication date: 1-Oct-2018
https://dl.acm.org/doi/10.1007/s10115-017-1149-7
Mampaey MVreeken JTatti N(2012)Summarizing data succinctly with the most informative itemsetsACM Transactions on Knowledge Discovery from Data (TKDD)10.1145/2382577.23825806:4(1-42)Online publication date: 18-Dec-2012
https://dl.acm.org/doi/10.1145/2382577.2382580
Tatti NVreeken J(2011)Comparing apples and orangesProceedings of the 2011 European conference on Machine learning and knowledge discovery in databases - Volume Part III10.5555/2034161.2034188(398-413)Online publication date: 5-Sep-2011
https://dl.acm.org/doi/10.5555/2034161.2034188
Mampaey MTatti NVreeken JApte CGhosh JSmyth P(2011)Tell me what i need to knowProceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining10.1145/2020408.2020499(573-581)Online publication date: 21-Aug-2011
https://dl.acm.org/doi/10.1145/2020408.2020499
Tatti NVreeken J(2011)Comparing apples and oranges measuring differences between data mining resultsProceedings of the 2011th European Conference on Machine Learning and Knowledge Discovery in Databases - Volume Part III10.1007/978-3-642-23808-6_26(398-413)Online publication date: 5-Sep-2011
https://dl.acm.org/doi/10.1007/978-3-642-23808-6_26
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