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FIMI
2004
175views Data Mining» more  FIMI 2004»
13 years 8 months ago
CT-PRO: A Bottom-Up Non Recursive Frequent Itemset Mining Algorithm Using Compressed FP-Tree Data Structure
Frequent itemset mining (FIM) is an essential part of association rules mining. Its application for other data mining tasks has also been recognized. It has been an active researc...
Yudho Giri Sucahyo, Raj P. Gopalan
DAWAK
2008
Springer
13 years 9 months ago
Efficient Approximate Mining of Frequent Patterns over Transactional Data Streams
Abstract. We investigate the problem of finding frequent patterns in a continuous stream of transactions. It is recognized that the approximate solutions are usually sufficient and...
Willie Ng, Manoranjan Dash
GFKL
2007
Springer
184views Data Mining» more  GFKL 2007»
13 years 11 months ago
FSMTree: An Efficient Algorithm for Mining Frequent Temporal Patterns
Research in the field of knowledge discovery from temporal data recently focused on a new type of data: interval sequences. In contrast to event sequences interval sequences contai...
Steffen Kempe, Jochen Hipp, Rudolf Kruse
DBA
2006
182views Database» more  DBA 2006»
13 years 8 months ago
Matrix Apriori: Speeding Up the Search for Frequent Patterns
This work discusses the problem of generating association rules from a set of transactions in a relational database, taking performance and accuracy of found results as the essent...
Judith Pavón, Sidney Viana, Santiago G&oacu...
SAC
2008
ACM
13 years 7 months ago
Mining fault-tolerant frequent patterns efficiently with powerful pruning
The mining of frequent patterns in databases has been studied for several years. However, the real-world data tends to be dirty and frequent pattern mining which extracts patterns...
Jhih-Jie Zeng, Guanling Lee, Chung-Chi Lee