2009 ProbabilisticFrequentItemsetMin

• (Bernecker et al., 2009) ⇒ Thomas Bernecker, Hans-Peter Kriegel, Matthias Renz, Florian Verhein, and Andreas Zuefle. (2009). “Probabilistic Frequent Itemset Mining in Uncertain Databases.” In: Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2009). doi:10.1145/1557019.1557039

Subject Headings:

Notes

• Categories and Subject Descriptors: H.2.8 Database Applications: Data Mining.
• General Terms: Algorithms, Theory

Cited By

• http://scholar.google.com/scholar?q=%22Probabilistic+frequent+itemset+mining+in+uncertain+databases%22+2009
• http://portal.acm.org/citation.cfm?doid=1557019.1557039&preflayout=flat#citedby

Quotes

Author Keywords

Uncertain Databases, Frequent Itemset Mining, Probabilistic Data, Probabilistic Frequent Itemsets

Abstract

Probabilistic frequent itemset mining in uncertain transaction databases semantically and computationally differs from traditional techniques applied to standard certain transaction databases. The consideration of existential uncertainty of item(sets), indicating the probability that an item(set) occurs in a transaction, makes traditional techniques inapplicable. In this paper, we introduce new probabilistic formulations of frequent itemsets based on possible world semantics. In this probabilistic context, an itemset X is called frequent if the probability that X occurs in at least minSup transactions is above a given threshold [math]\displaystyle{ \tau }[/math]. To the best of our knowledge, this is the first approach addressing this problem under possible worlds semantics. In consideration of the probabilistic formulations, we present a framework which is able to solve the Probabilistic Frequent Itemset Mining (PFIM) problem efficiently. An extensive experimental evaluation investigates the impact of our proposed techniques and shows that our approach is orders of magnitude faster than straight-forward approaches.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2009 ProbabilisticFrequentItemsetMin	Thomas Bernecker Andreas Zuefle Hans-Peter Kriegel Matthias Renz Florian Verhein			Probabilistic Frequent Itemset Mining in Uncertain Databases		KDD-2009 Proceedings		10.1145/1557019.1557039		2009