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» A Hidden Markov Model for the TREC Novelty Task
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COLING
2008
14 years 11 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
75
Voted
ICPR
2006
IEEE
15 years 10 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
14 years 11 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
14 years 11 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»
14 years 9 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