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» Discovering and Processing Sequential Patterns in Databases
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103
Voted
KDD
2005
ACM
153views Data Mining» more  KDD 2005»
15 years 10 months ago
Improving discriminative sequential learning with rare--but--important associations
Discriminative sequential learning models like Conditional Random Fields (CRFs) have achieved significant success in several areas such as natural language processing, information...
Xuan Hieu Phan, Minh Le Nguyen, Tu Bao Ho, Susumu ...
ICDE
2009
IEEE
176views Database» more  ICDE 2009»
15 years 11 months ago
Discovering Conditional Functional Dependencies
This paper investigates the discovery of conditional functional dependencies (CFDs). CFDs are a recent extension of functional dependencies (FDs) by supporting patterns of semantic...
Wenfei Fan, Floris Geerts, Laks V. S. Lakshmanan, ...
ICPADS
2006
IEEE
15 years 3 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
89
Voted
KDD
2007
ACM
151views Data Mining» more  KDD 2007»
15 years 10 months ago
Efficient mining of iterative patterns for software specification discovery
Studies have shown that program comprehension takes up to 45% of software development costs. Such high costs are caused by the lack-of documented specification and further aggrava...
Chao Liu 0001, David Lo, Siau-Cheng Khoo
PKDD
2005
Springer
138views Data Mining» more  PKDD 2005»
15 years 3 months ago
Indexed Bit Map (IBM) for Mining Frequent Sequences
Sequential pattern mining has been an emerging problem in data mining. In this paper, we propose a new algorithm for mining frequent sequences. It processes only one scan of the da...
Lionel Savary, Karine Zeitouni