NDLI: Research on Transaction-Item Association Matrix Mining Algorithm in Large-scale Transaction Database

Content Provider	IEEE Xplore Digital Library
Author	Chengmin Wang Weiqing Sun Tieyan Zhang Yan Zhang
Copyright Year	2009
Abstract	To increase the efficiency of data mining is the research emphasis in this field at present. Through the establishment of transaction-item association matrix, this paper changes the process of association rule mining to elementary matrix operation, which makes the process of data mining clear and simple. Compared with algorithms like Apriori, this method avoids the demerit of traversing the database repetitiously, and increases the efficiency of association rule mining obviously in the use of sparse storage technique for large-scale matrix. To incremental type of transaction matrix, it can also make the maintainment of association rule more convenient in the use of partitioning calculation technique of matrix. The transaction-item association matrix proposed in this paper can be seemed as the mathematical foundation of association rule mining algorithm.
Starting Page	113
Ending Page	117
File Size	324447
Page Count	5
File Format	PDF
ISBN	9780769537351
DOI	10.1109/FSKD.2009.88
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-08-14
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Knowledge engineering Itemsets Data engineering Large-scale systems Transaction databases Data mining Association rules Sparse matrices Matrix decomposition Fuzzy systems
Content Type	Text
Resource Type	Article

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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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