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Computational complexity of itemset frequency satisfiability
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Proceedings of the twenty-third ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems table of contents
Paris, France
SESSION: Clustering, data mining, approximations table of contents
Pages: 143 - 154  
Year of Publication: 2004
ISBN:158113858X
Author
Toon Calders  University of Antwerp, Belgium
Sponsors
SIGACT: ACM Special Interest Group on Algorithms and Computation Theory
SIGMOD: ACM Special Interest Group on Management of Data
SIGART: ACM Special Interest Group on Artificial Intelligence
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 3,   Downloads (12 Months): 30,   Citation Count: 8
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ABSTRACT

Computing frequent itemsets is one of the most prominent problems in data mining. We introduce a new, related problem, called FREQSAT: given some itemset-interval pairs, does there exist a database such that for every pair the frequency of the itemset falls in the interval? It is shown in this paper that FREQSAT is not finitely axiomatizable and that it is NP-complete. We also study cases in which other characteristics of the database are given as well. These characteristics can complicate FREQSAT even more. For example, when the maximal number of duplicates of a transaction is known, FREQSAT becomes PP-hard. We describe applications of FREQSAT in frequent itemset mining algorithms and privacy in data mining.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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T. Calders, Deducing bounds on the support of itemsets. In Database Support for Data Mining Applications, LNCS 2682, Springer, to appear 2004.
 
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T. Mielikäinen. On inverse frequent set mining. In Workshop on Privacy Preserving Data Mining, 2003.
 
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CITED BY  8