Sciweavers

ACL
2009
13 years 10 months ago
Hidden Markov Tree Model in Dependency-based Machine Translation
We would like to draw attention to Hidden Markov Tree Models (HMTM), which are to our knowledge still unexploited in the field of Computational Linguistics, in spite of highly suc...
Zdenek Zabokrtský, Martin Popel
NIPS
2003
14 years 1 months ago
Markov Models for Automated ECG Interval Analysis
We examine the use of hidden Markov and hidden semi-Markov models for automatically segmenting an electrocardiogram waveform into its constituent waveform features. An undecimated...
Nicholas P. Hughes, Lionel Tarassenko, Stephen J. ...
EMNLP
2007
14 years 2 months ago
Bootstrapping Information Extraction from Field Books
We present two machine learning approaches to information extraction from semi-structured documents that can be used if no annotated training data are available, but there does ex...
Sander Canisius, Caroline Sporleder
WIDM
2004
ACM
14 years 6 months ago
Probabilistic models for focused web crawling
A Focused crawler must use information gleaned from previously crawled page sequences to estimate the relevance of a newly seen URL. Therefore, good performance depends on powerfu...
Hongyu Liu, Evangelos E. Milios, Jeannette Janssen
GW
2005
Springer
129views Biometrics» more  GW 2005»
14 years 6 months ago
Visual Sign Language Recognition Based on HMMs and Auto-regressive HMMs
Abstract. A sign language recognition system based on Hidden Markov Models(HMMs) and Auto-regressive Hidden Markov Models(ARHMMs) has been proposed in this paper. ARHMMs fully cons...
Xiaolin Yang, Feng Jiang, Han Liu, Hongxun Yao, We...
MICAI
2007
Springer
14 years 6 months ago
An EM Algorithm to Learn Sequences in the Wavelet Domain
The wavelet transform has been used for feature extraction in many applications of pattern recognition. However, in general the learning algorithms are not designed taking into acc...
Diego H. Milone, Leandro E. Di Persia
ICDM
2008
IEEE
230views Data Mining» more  ICDM 2008»
14 years 7 months ago
Evolutionary Clustering by Hierarchical Dirichlet Process with Hidden Markov State
This paper studies evolutionary clustering, which is a recently hot topic with many important applications, noticeably in social network analysis. In this paper, based on the rece...
Tianbing Xu, Zhongfei (Mark) Zhang, Philip S. Yu, ...