Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Mining frequent patterns without candidate generation
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Scalable, Distributed and Dynamic Mining of Association Rules
HiPC '00 Proceedings of the 7th International Conference on High Performance Computing
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Mining Frequent Patterns without Candidate Generation: A Frequent-Pattern Tree Approach
Data Mining and Knowledge Discovery
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
ACS'07 Proceedings of the 7th Conference on 7th WSEAS International Conference on Applied Computer Science - Volume 7
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The abstraction based algorithms read databases in sequential order and then construct abstraction of the database in memory. Given any database with n attributes, it is possible to read the same in n! ways. These different n! ways lead to abstractions of different sizes. In this paper, for a given a set of transactions D, we find the sequence or order of the attributes in which the database is read, a representation which is compact than PC-tree, can be obtained in the memory.