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» Compression-based data mining of sequential data
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ICDM
2010
IEEE
201views Data Mining» more  ICDM 2010»
13 years 5 months ago
Mining Closed Strict Episodes
Discovering patterns in a sequence is an important aspect of data mining. One popular choice of such patterns are episodes, patterns in sequential data describing events that often...
Nikolaj Tatti, Boris Cule
TDP
2010
166views more  TDP 2010»
13 years 2 months ago
Communication-Efficient Privacy-Preserving Clustering
The ability to store vast quantities of data and the emergence of high speed networking have led to intense interest in distributed data mining. However, privacy concerns, as well ...
Geetha Jagannathan, Krishnan Pillaipakkamnatt, Reb...
PAKDD
2000
ACM
124views Data Mining» more  PAKDD 2000»
13 years 11 months ago
Feature Selection for Clustering
In clustering, global feature selection algorithms attempt to select a common feature subset that is relevant to all clusters. Consequently, they are not able to identify individu...
Manoranjan Dash, Huan Liu
KDD
2007
ACM
151views Data Mining» more  KDD 2007»
14 years 8 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
OSDI
2008
ACM
13 years 9 months ago
DryadLINQ: A System for General-Purpose Distributed Data-Parallel Computing Using a High-Level Language
DryadLINQ is a system and a set of language extensions that enable a new programming model for large scale distributed computing. It generalizes previous execution environments su...
Yuan Yu, Michael Isard, Dennis Fetterly, Mihai Bud...