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ACL
2006
15 years 1 months ago
Segment-Based Hidden Markov Models for Information Extraction
Hidden Markov models (HMMs) are powerful statistical models that have found successful applications in Information Extraction (IE). In current approaches to applying HMMs to IE, a...
Zhenmei Gu, Nick Cercone
ICPR
2002
IEEE
16 years 21 days ago
A Two Level Classifier Process for Audio Segmentation
We are dealing in this paper with audio segmentation. We propose a two level segmentation process that enables the audio tracks to be sampled in short sequences which are classifi...
Benjamin Maillard, Nicole Vincent, Sébastie...
85
Voted
ECML
2006
Springer
15 years 3 months ago
PAC-Learning of Markov Models with Hidden State
The standard approach for learning Markov Models with Hidden State uses the Expectation-Maximization framework. While this approach had a significant impact on several practical ap...
Ricard Gavaldà, Philipp W. Keller, Joelle P...
JMLR
2010
185views more  JMLR 2010»
14 years 6 months ago
HMMPayl: an application of HMM to the analysis of the HTTP Payload
Zero-days attacks are one of the most dangerous threats against computer networks. These, by definition, are attacks never seen before. Thus, defense tools based on a database of ...
Davide Ariu, Giorgio Giacinto
122
Voted
BMCBI
2004
177views more  BMCBI 2004»
14 years 11 months ago
Gapped alignment of protein sequence motifs through Monte Carlo optimization of a hidden Markov model
Background: Certain protein families are highly conserved across distantly related organisms and belong to large and functionally diverse superfamilies. The patterns of conservati...
Andrew F. Neuwald, Jun S. Liu