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» An Iterative Method for Mining Frequent Temporal Patterns
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TKDE
2008
128views more  TKDE 2008»
13 years 8 months ago
Mixed-Drove Spatiotemporal Co-Occurrence Pattern Mining
Mixed-drove spatiotemporal co-occurrence patterns (MDCOPs) represent subsets of two or more different object-types whose instances are often located in spatial and temporal proximi...
Mete Celik, Shashi Shekhar, James P. Rogers, James...
PVLDB
2008
107views more  PVLDB 2008»
13 years 8 months ago
Finding relevant patterns in bursty sequences
Sequence data is ubiquitous and finding frequent sequences in a large database is one of the most common problems when analyzing sequence data. Unfortunately many sources of seque...
Alexander Lachmann, Mirek Riedewald
SOFTWARE
2002
13 years 8 months ago
Temporal Probabilistic Concepts from Heterogeneous Data Sequences
We consider the problem of characterisation of sequences of heterogeneous symbolic data that arise from a common underlying temporal pattern. The data, which are subject to impreci...
Sally I. McClean, Bryan W. Scotney, Fiona Palmer
EDBT
2011
ACM
199views Database» more  EDBT 2011»
13 years 5 days ago
Finding closed frequent item sets by intersecting transactions
Most known frequent item set mining algorithms work by enumerating candidate item sets and pruning infrequent candidates. An alternative method, which works by intersecting transa...
Christian Borgelt, Xiaoyuan Yang, Rubén Nog...
GRC
2010
IEEE
13 years 9 months ago
Local Pattern Mining from Sequences Using Rough Set Theory
Abstract--Sequential pattern mining is a crucial but challenging task in many applications, e.g., analyzing the behaviors of data in transactions and discovering frequent patterns ...
Ken Kaneiwa, Yasuo Kudo