Mining periodic behaviors for moving objects
Periodicity is a frequently happening phenomenon for moving objects. Finding periodic
behaviors is essential to understanding object movements. However, periodic behaviors …
behaviors is essential to understanding object movements. However, periodic behaviors …
Top-k Self-Adaptive Contrast Sequential Pattern Mining
For sequence classification, an important issue is to find discriminative features, where
sequential pattern mining (SPM) is often used to find frequent patterns from sequences as …
sequential pattern mining (SPM) is often used to find frequent patterns from sequences as …
NetNCSP: Nonoverlap** closed sequential pattern mining
Sequential pattern mining (SPM) has been applied in many fields. However, traditional SPM
neglects the pattern repetition in sequence. To solve this problem, gap constraint SPM was …
neglects the pattern repetition in sequence. To solve this problem, gap constraint SPM was …
HAOP-Miner: Self-adaptive high-average utility one-off sequential pattern mining
One-off sequential pattern mining (SPM)(or SPM under the one-off condition) is a kind of
repetitive SPM with gap constraints, and has been widely applied in many fields. However …
repetitive SPM with gap constraints, and has been widely applied in many fields. However …
Mining minimal distinguishing subsequence patterns with gap constraints
Discovering contrasts between collections of data is an important task in data mining. In this
paper, we introduce a new type of contrast pattern, called a Minimal Distinguishing …
paper, we introduce a new type of contrast pattern, called a Minimal Distinguishing …
NOSEP: Nonoverlap** sequence pattern mining with gap constraints
Sequence pattern mining aims to discover frequent subsequences as patterns in a single
sequence or a sequence database. By combining gap constraints (or flexible wildcards) …
sequence or a sequence database. By combining gap constraints (or flexible wildcards) …
Hierarchical trajectory clustering for spatio-temporal periodic pattern mining
Spatio-temporal periodic pattern mining is to find temporal regularities for interesting places.
Many real world spatio-temporal phenomena present sequential and hierarchical nature …
Many real world spatio-temporal phenomena present sequential and hierarchical nature …
NetNMSP: Nonoverlap** maximal sequential pattern mining
Nonoverlap** sequential pattern mining, as a kind of repetitive sequential pattern mining
with gap constraints, can find more valuable patterns. Traditional algorithms focused on …
with gap constraints, can find more valuable patterns. Traditional algorithms focused on …
Mining local periodic patterns in a discrete sequence
Periodic frequent patterns are sets of events or items that periodically appear in a sequence
of events or transactions. Many algorithms have been designed to identify periodic frequent …
of events or transactions. Many algorithms have been designed to identify periodic frequent …
Efficient mining of closed repetitive gapped subsequences from a sequence database
There is a huge wealth of sequence data available, for example, customer purchase
histories, program execution traces, DNA, and protein sequences. Analyzing this wealth of …
histories, program execution traces, DNA, and protein sequences. Analyzing this wealth of …