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» A Hidden Markov Model for the TREC Novelty Task
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COLING
2008
13 years 9 months ago
Homotopy-Based Semi-Supervised Hidden Markov Models for Sequence Labeling
This paper explores the use of the homotopy method for training a semi-supervised Hidden Markov Model (HMM) used for sequence labeling. We provide a novel polynomial-time algorith...
Gholamreza Haffari, Anoop Sarkar
ICPR
2006
IEEE
14 years 8 months ago
Protein Fold Recognition using a Structural Hidden Markov Model
Protein fold recognition has been the focus of computational biologists for many years. In order to map a protein primary structure to its correct 3D fold, we introduce in this pa...
Djamel Bouchaffra, Jun Tan
UAI
2008
13 years 9 months ago
Learning Hidden Markov Models for Regression using Path Aggregation
We consider the task of learning mappings from sequential data to real-valued responses. We present and evaluate an approach to learning a type of hidden Markov model (HMM) for re...
Keith Noto, Mark Craven
ECIR
2006
Springer
13 years 9 months ago
Sentence Retrieval with LSI and Topic Identification
This paper presents two sentence retrieval methods. We adopt the task definition done in the TREC Novelty Track: sentence retrieval consists in the extraction of the relevant sente...
David Parapar, Alvaro Barreiro
BMCBI
2004
208views more  BMCBI 2004»
13 years 7 months ago
Using 3D Hidden Markov Models that explicitly represent spatial coordinates to model and compare protein structures
Background: Hidden Markov Models (HMMs) have proven very useful in computational biology for such applications as sequence pattern matching, gene-finding, and structure prediction...
Vadim Alexandrov, Mark Gerstein