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FIMI
2003
170views Data Mining» more  FIMI 2003»
14 years 11 months ago
kDCI: a Multi-Strategy Algorithm for Mining Frequent Sets
This paper presents the implementation of kDCI, an enhancement of DCI [10], a scalable algorithm for discovering frequent sets in large databases. The main contribution of kDCI re...
Salvatore Orlando, Claudio Lucchese, Paolo Palmeri...
ADMA
2009
Springer
121views Data Mining» more  ADMA 2009»
14 years 7 months ago
Quantitative Comparison of Similarity Measure and Entropy for Fuzzy Sets
Comparison and data analysis to the similarity measures and entropy for fuzzy sets are studied. The distance proportional value between the fuzzy set and the corresponding crisp se...
Hongmei Wang, Sanghyuk Lee, Jaehyung Kim
KDD
2002
ACM
140views Data Mining» more  KDD 2002»
15 years 10 months ago
Mining frequent item sets by opportunistic projection
In this paper, we present a novel algorithm OpportuneProject for mining complete set of frequent item sets by projecting databases to grow a frequent item set tree. Our algorithm ...
Junqiang Liu, Yunhe Pan, Ke Wang, Jiawei Han
RSFDGRC
2011
Springer
287views Data Mining» more  RSFDGRC 2011»
14 years 18 days ago
Towards Faster Estimation of Statistics and ODEs Under Interval, P-Box, and Fuzzy Uncertainty: From Interval Computations to Rou
Interval computations estimate the uncertainty of the result of data processing in situations in which we only know the upper bounds ∆ on the measurement errors. In interval comp...
Vladik Kreinovich
SIGMOD
1993
ACM
134views Database» more  SIGMOD 1993»
15 years 1 months ago
Mining Association Rules between Sets of Items in Large Databases
We are given a large database of customer transactions. Each transaction consists of items purchased by a customer in a visit. We present an e cient algorithm that generates all s...
Rakesh Agrawal, Tomasz Imielinski, Arun N. Swami