Abstract
We describe a Metropolis-Hastings algorithm for sampling formal concepts, i.e., closed (item-) sets, according to any desired strictly positive distribution. Important applications are (a) estimating the number of all formal concepts as well as (b) discovering any number of interesting, non-redundant, and representative local patterns. Setting (a) can be used for estimating the runtime of algorithms examining all formal concepts. An application of setting (b) is the construction of data mining systems that do not require any user-specified threshold like minimum frequency or confidence.
Original language | English |
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Pages | 177-188 |
Number of pages | 12 |
DOIs | |
State | Published - 2010 |
Externally published | Yes |
Event | 10th SIAM International Conference on Data Mining, SDM 2010 - Columbus, OH, United States Duration: 29 Apr 2010 → 1 May 2010 |
Conference
Conference | 10th SIAM International Conference on Data Mining, SDM 2010 |
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Country/Territory | United States |
City | Columbus, OH |
Period | 29/04/10 → 1/05/10 |
ASJC Scopus subject areas
- Software