19 search results - page 3 / 4 » FIT: A Fast Algorithm for Discovering Frequent Itemsets in L... |
IS
2007
13 years 5 months ago
2007
As data mining techniques are being increasingly applied to non-traditional domains, existing approaches for finding frequent itemsets cannot be used as they cannot model the req...
FIMI
2004
13 years 6 months ago
2004
In this paper, we present an ongoing work to discover maximal frequent itemsets in a transactional database. We propose an algorithm called ABS for Adaptive Borders Search, which ...
ADMA
2005
Springer
13 years 7 months ago
2005
Springer
Efficient discovery of frequent patterns from large databases is an active research area in data mining with broad applications in industry and deep implications in many areas of d...
PPOPP
2005
ACM
13 years 10 months ago
2005
ACM
The goal of data mining algorithm is to discover useful information embedded in large databases. Frequent itemset mining and sequential pattern mining are two important data minin...
ICDE
2009
IEEE
14 years 7 months ago
2009
IEEE
This paper investigates the discovery of conditional functional dependencies (CFDs). CFDs are a recent extension of functional dependencies (FDs) by supporting patterns of semantic...