NDLI: Database Encoding and An Anti-Apriori Algorithm for Association Rules Mining

Content Provider	IEEE Xplore Digital Library
Author	Tong Wang Pi-Lian He
Copyright Year	2006
Description	Author affiliation: Vocational Technique Instruction Coll., Tianjin Univ. (Tong Wang)
Abstract	A method for encoding database is put forward in this paper. By this way, a record is denoted by only one binary number and so the size of the database is reduced sharply. If the database-encoding algorithm is used into some known modified algorithms, the efficiency will be improved remarkably. At the meantime, a new algorithm, anti-Apriori, which based on the proposed encoding method is introduced either. By using some properties of numbers, the itemsets of the database can be transformed into numerical fields. Different from the Apriori algorithm, the new one discovers the association rules from the largest frequent itemset at first, and then all sub itemset, which are also frequent, will be gained without any farther calculation, and all the other small frequent itemset that must be generated in the Apriori be omitted, and the times of the database scan is also reduced. Test results show the new algorithm based on the encoding database has a lower complexity of time and space
Sponsorship	IEEE Syst., Man and Cybernetics Hebei Univ.
Starting Page	1195
Ending Page	1198
File Size	267852
Page Count	4
File Format	PDF
ISBN	1424400619
DOI	10.1109/ICMLC.2006.258604
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-08-13
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Encoding Association rules Data mining Itemsets Machine learning algorithms Educational institutions Marketing and sales Transaction databases Helium Computer science database encoding Anti-Apriori algorithm association rules data mining
Content Type	Text
Resource Type	Article

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