Paper Info
Title
Research on Transaction-Item Association Matrix Mining Algorithm in Large-scale Transaction Database
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.
Year
DOI
Venue
2009
10.1109/FSKD.2009.88
FSKD (2)
Keywords
Field
DocType
association rule mining algorithm,transaction-item association matrix mining,apriori,large-scale transaction database,transaction-item association matrix,association rule,elementary matrix operation,transaction processing,transaction matrix,paper change,association rule mining,data mining,very large databases,large-scale matrix,data mining efficiency,partitioning calculation technique,sparse storage technique,association rules,sparse matrices,algorithm design and analysis
Transaction processing,Data mining,Algorithm design,Elementary matrix,Matrix (mathematics),Computer science,Apriori algorithm,FSA-Red Algorithm,Association rule learning,Sparse matrix
Conference
Volume
ISBN
Citations 
2
978-0-7695-3735-1
0
PageRank 
References 
Authors
0.34
9
4
Name
Order
Citations
PageRank
Chengmin Wang1448.30
Weiqing Sun223415.89
Tieyan Zhang3652.66
Yan Zhang400.34