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PVLDB
2008
107views more  PVLDB 2008»
15 years 4 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
PKDD
2010
Springer
150views Data Mining» more  PKDD 2010»
15 years 2 months ago
Virus Propagation on Time-Varying Networks: Theory and Immunization Algorithms
Given a contact network that changes over time (say, day vs night connectivity), and the SIS (susceptible/infected/susceptible, flu like) virus propagation model, what can we say ...
B. Aditya Prakash, Hanghang Tong, Nicholas Valler,...
ICDM
2006
IEEE
147views Data Mining» more  ICDM 2006»
15 years 10 months ago
Adaptive Parallel Graph Mining for CMP Architectures
Mining graph data is an increasingly popular challenge, which has practical applications in many areas, including molecular substructure discovery, web link analysis, fraud detect...
Gregory Buehrer, Srinivasan Parthasarathy, Yen-Kua...
ICDM
2003
IEEE
141views Data Mining» more  ICDM 2003»
15 years 9 months ago
Association Rule Mining in Peer-to-Peer Systems
We extend the problem of association rule mining – a key data mining problem – to systems in which the database is partitioned among a very large number of computers that are ...
Ran Wolff, Assaf Schuster
DAWAK
2004
Springer
15 years 10 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...