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ICDM
2009
IEEE
233views Data Mining» more  ICDM 2009»
14 years 2 months ago
Semi-Supervised Sequence Labeling with Self-Learned Features
—Typical information extraction (IE) systems can be seen as tasks assigning labels to words in a natural language sequence. The performance is restricted by the availability of l...
Yanjun Qi, Pavel Kuksa, Ronan Collobert, Kunihiko ...
BMCBI
2008
108views more  BMCBI 2008»
13 years 7 months ago
An analysis of the positional distribution of DNA motifs in promoter regions and its biological relevance
Background: Motif finding algorithms have developed in their ability to use computationally efficient methods to detect patterns in biological sequences. However the posterior cla...
Ana C. Casimiro, Susana Vinga, Ana T. Freitas, Arl...
SDM
2004
SIAM
162views Data Mining» more  SDM 2004»
13 years 8 months ago
Subspace Clustering of High Dimensional Data
Clustering suffers from the curse of dimensionality, and similarity functions that use all input features with equal relevance may not be effective. We introduce an algorithm that...
Carlotta Domeniconi, Dimitris Papadopoulos, Dimitr...
BMCBI
2005
122views more  BMCBI 2005»
13 years 7 months ago
FACT - a framework for the functional interpretation of high-throughput experiments
Background: Interpreting the results of high-throughput experiments, such as those obtained from DNA-microarrays, is an often time-consuming task due to the high number of data-po...
Felix Kokocinski, Nicolas Delhomme, Gunnar Wrobel,...
JCB
2007
118views more  JCB 2007»
13 years 7 months ago
Discovering Topological Motifs Using a Compact Notation
Discovering topological motifs or common topologies in one or more graphs is an important as well as an interesting problem. It had been classically viewed as the subgraph isomorp...
Laxmi Parida