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KDD
2009
ACM
207views Data Mining» more  KDD 2009»
14 years 8 months ago
DynaMMo: mining and summarization of coevolving sequences with missing values
Given multiple time sequences with missing values, we propose DynaMMo which summarizes, compresses, and finds latent variables. The idea is to discover hidden variables and learn ...
Lei Li, James McCann, Nancy S. Pollard, Christos F...
CIKM
2004
Springer
14 years 1 months ago
Scalable sequential pattern mining for biological sequences
Biosequences typically have a small alphabet, a long length, and patterns containing gaps (i.e., “don’t care”) of arbitrary size. Mining frequent patterns in such sequences ...
Ke Wang, Yabo Xu, Jeffrey Xu Yu
BMCBI
2010
123views more  BMCBI 2010»
13 years 8 months ago
Decoding HMMs using the k best paths: algorithms and applications
Background: Traditional algorithms for hidden Markov model decoding seek to maximize either the probability of a state path or the number of positions of a sequence assigned to th...
Daniel G. Brown 0001, Daniil Golod
DAC
1997
ACM
14 years 3 days ago
Multilevel Hypergraph Partitioning: Application in VLSI Domain
In this paper, we present a new hypergraph partitioning algorithm that is based on the multilevel paradigm. In the multilevel paradigm, a sequence of successively coarser hypergra...
George Karypis, Rajat Aggarwal, Vipin Kumar, Shash...
JCP
2006
173views more  JCP 2006»
13 years 8 months ago
Database Intrusion Detection using Weighted Sequence Mining
Data mining is widely used to identify interesting, potentially useful and understandable patterns from a large data repository. With many organizations focusing on webbased on-lin...
Abhinav Srivastava, Shamik Sural, Arun K. Majumdar