NDLI: Randomly sampling maximal itemsets

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Randomly sampling maximal itemsets

Content Provider	ACM Digital Library
Author	Goethals, Bart Moens, Sandy
Abstract	Pattern mining techniques generally enumerate lots of uninteresting and redundant patterns. To obtain less redundant collections, techniques exist that give condensed representations of these collections. However, the proposed techniques often rely on complete enumeration of the pattern space, which can be prohibitive in terms of time and memory. Sampling can be used to filter the output space of patterns without explicit enumeration. We propose a framework for random sampling of maximal itemsets from transactional databases. The presented framework can use any monotonically decreasing measure as interestingness criteria for this purpose. Moreover, we use an approximation measure to guide the search for maximal sets to different parts of the output space. We show in our experiments that the method can rapidly generate small collections of patterns with good quality. The sampling framework has been implemented in the interactive visual data mining tool called $MIME^{1},$ as such enabling users to quickly sample a collection of patterns and analyze the results.
Starting Page	79
Ending Page	86
Page Count	8
File Format	PDF
ISBN	9781450323291
DOI	10.1145/2501511.2501523
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2013-08-11
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Random walks Output space sampling Maximal itemsets
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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