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» Incremental Mining of Sequential Patterns in Large Databases
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ICPADS
2006
IEEE
14 years 1 months ago
Parallel Leap: Large-Scale Maximal Pattern Mining in a Distributed Environment
When computationally feasible, mining extremely large databases produces tremendously large numbers of frequent patterns. In many cases, it is impractical to mine those datasets d...
Mohammad El-Hajj, Osmar R. Zaïane
DAWAK
2005
Springer
13 years 9 months ago
Incremental Data Mining Using Concurrent Online Refresh of Materialized Data Mining Views
Abstract. Data mining is an iterative process. Users issue series of similar data mining queries, in each consecutive run slightly modifying either the definition of the mined dat...
Mikolaj Morzy, Tadeusz Morzy, Marek Wojciechowski,...
SBACPAD
2003
IEEE
180views Hardware» more  SBACPAD 2003»
14 years 23 days ago
New Parallel Algorithms for Frequent Itemset Mining in Very Large Databases
Frequent itemset mining is a classic problem in data mining. It is a non-supervised process which concerns in finding frequent patterns (or itemsets) hidden in large volumes of d...
Adriano Veloso, Wagner Meira Jr., Srinivasan Parth...
ACMSE
2008
ACM
13 years 9 months ago
Mining frequent sequential patterns with first-occurrence forests
In this paper, a new pattern-growth algorithm is presented to mine frequent sequential patterns using First-Occurrence Forests (FOF). This algorithm uses a simple list of pointers...
Erich Allen Peterson, Peiyi Tang