NDLI: A fast algorithm for cofactor implication checking and its application for knowledge discovery

Content Provider	IEEE Xplore Digital Library
Author	Minato, S.-i.
Copyright Year	2008
Description	Author affiliation: Grad. Sch. of Inf. Sci. & Technol., Hokkaido Univ., Sapporo (Minato, S.-i.)
Abstract	In this paper, we propose a new method for discovering hidden information from large-scale transaction databases by considering a property of cofactor implication. Cofactor implication is an extension or generalization of symmetric itemsets, which has been presented recently. Here we discuss the meaning of cofactor implication for the data mining applications, and show an efficient algorithm of extracting all non-trivial item pairs with cofactor implication by using Zero-suppressed Binary Decision Diagrams (ZBDDs). We show an experimental result to see how many itemsets can be extracted by using cofactor implication, compared with symmetric item set mining. Our result shows that the use of cofactor implication has a possibility of discovering a new aspect of structural information hidden in the databases.
Starting Page	53
Ending Page	58
File Size	273029
Page Count	6
File Format	PDF
ISBN	9781424423576
DOI	10.1109/CIT.2008.4594649
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-07-08
Publisher Place	Australia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis Boolean functions Databases Itemsets Data structures Transaction databases Data mining
Content Type	Text
Resource Type	Article

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