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WSDM
2010
ACM
322views Data Mining» more  WSDM 2010»
15 years 10 months ago
Inferring Search Behaviors Using Partially Observable Markov (POM) Model
This article describes an application of the partially observable Markov (POM) model to the analysis of a large scale commercial web search log. Mathematically, POM is a variant o...
Kuansan Wang, Nikolas Gloy, Xiaolong Li
NAACL
2007
15 years 2 months ago
Applying Many-to-Many Alignments and Hidden Markov Models to Letter-to-Phoneme Conversion
Letter-to-phoneme conversion generally requires aligned training data of letters and phonemes. Typically, the alignments are limited to one-to-one alignments. We present a novel t...
Sittichai Jiampojamarn, Grzegorz Kondrak, Tarek Sh...
BMCBI
2010
229views more  BMCBI 2010»
15 years 1 months ago
Mocapy++ - A toolkit for inference and learning in dynamic Bayesian networks
Background: Mocapy++ is a toolkit for parameter learning and inference in dynamic Bayesian networks (DBNs). It supports a wide range of DBN architectures and probability distribut...
Martin Paluszewski, Thomas Hamelryck
CN
2004
103views more  CN 2004»
15 years 1 months ago
Modeling IP traffic: joint characterization of packet arrivals and packet sizes using BMAPs
This paper proposes a traffic model and a parameter fitting procedure that are capable of achieving accurate prediction of the queuing behavior for IP traffic exhibiting long-rang...
Paulo Salvador, António Pacheco, Rui Valada...
BMCBI
2010
123views more  BMCBI 2010»
14 years 8 months ago
Predicting conserved protein motifs with Sub-HMMs
Background: Profile HMMs (hidden Markov models) provide effective methods for modeling the conserved regions of protein families. A limitation of the resulting domain models is th...
Kevin Horan, Christian R. Shelton, Thomas Girke