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DAWAK
2004
Springer
15 years 7 months ago
Mining Maximal Frequently Changing Subtree Patterns from XML Documents
Abstract. Due to the dynamic nature of online information, XML documents typically evolve over time. The change of the data values or structures of an XML document may exhibit some...
Ling Chen 0002, Sourav S. Bhowmick, Liang-Tien Chi...
SIGKDD
2008
113views more  SIGKDD 2008»
15 years 1 months ago
On exploiting the power of time in data mining
We introduce the new paradigm of Change Mining as data mining over a volatile, evolving world with the objective of understanding change. While there is much work on incremental m...
Mirko Böttcher, Frank Höppner, Myra Spil...
ICIP
2005
IEEE
15 years 7 months ago
Mining arbitrary-length repeated patterns in television broadcast
Mining repeated patterns in television broadcast is important to advertisers in tracking a large number of television commercials. It can also benefit long-term archival of telev...
Sen-Ching S. Cheung, Thinh Nguyen
SAC
2010
ACM
15 years 8 months ago
A generative pattern model for mining binary datasets
In many application fields, huge binary datasets modeling real life-phenomena are daily produced. The dataset records are usually associated with observations of some events, and...
Claudio Lucchese, Salvatore Orlando, Raffaele Pere...
ICTAI
2006
IEEE
15 years 7 months ago
Sustained Emerging Spatio-Temporal Co-occurrence Pattern Mining: A Summary of Results
Sustained emerging spatio-temporal co-occurrence patterns (SECOPs) represent subsets of object-types that are increasingly located together in space and time. Discovering SECOPs i...
Mete Celik, Shashi Shekhar, James P. Rogers, James...