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WSDM
2010
ACM
322views Data Mining» more  WSDM 2010»
15 years 7 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
14 years 11 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»
14 years 10 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»
14 years 9 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 4 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