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» Mining Surprising Patterns Using Temporal Description Length
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TCSV
2008
150views more  TCSV 2008»
13 years 6 months ago
Mining Recurring Events Through Forest Growing
Recurring events are short temporal patterns that consist of multiple instances in the target database. Without any a priori knowledge of the recurring events, in terms of their le...
Junsong Yuan, Jingjing Meng, Ying Wu, Jiebo Luo
KDD
2007
ACM
151views Data Mining» more  KDD 2007»
14 years 6 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
SDM
2008
SIAM
125views Data Mining» more  SDM 2008»
13 years 7 months ago
Mining and Ranking Generators of Sequential Patterns
Sequential pattern mining first proposed by Agrawal and Srikant has received intensive research due to its wide range applicability in many real-life domains. Various improvements...
David Lo, Siau-Cheng Khoo, Jinyan Li
ICDM
2005
IEEE
133views Data Mining» more  ICDM 2005»
13 years 12 months ago
Parameter-Free Spatial Data Mining Using MDL
Consider spatial data consisting of a set of binary features taking values over a collection of spatial extents (grid cells). We propose a method that simultaneously finds spatia...
Spiros Papadimitriou, Aristides Gionis, Panayiotis...
SAC
2004
ACM
13 years 11 months ago
A new algorithm for gap constrained sequence mining
The sequence mining problem consists in finding frequent sequential patterns in a database of time-stamped events. Several application domains require limiting the maximum tempor...
Salvatore Orlando, Raffaele Perego, Claudio Silves...