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» Learning to Align: A Statistical Approach
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EMNLP
2004
13 years 9 months ago
A New Approach for English-Chinese Named Entity Alignment
Traditional word alignment approaches cannot come up with satisfactory results for Named Entities. In this paper, we propose a novel approach using a maximum entropy model for nam...
Donghui Feng, Yajuan Lü, Ming Zhou
BMCBI
2010
133views more  BMCBI 2010»
13 years 7 months ago
Improving de novo sequence assembly using machine learning and comparative genomics for overlap correction
Background: With the rapid expansion of DNA sequencing databases, it is now feasible to identify relevant information from prior sequencing projects and completed genomes and appl...
Lance E. Palmer, Mathäus Dejori, Randall A. B...
ACL
2006
13 years 9 months ago
Semi-Supervised Training for Statistical Word Alignment
We introduce a semi-supervised approach to training for statistical machine translation that alternates the traditional Expectation Maximization step that is applied on a large tr...
Alexander Fraser, Daniel Marcu
CIARP
2009
Springer
13 years 5 months ago
Incorporating Linguistic Information to Statistical Word-Level Alignment
Abstract. Parallel texts are enriched by alignment algorithms, thus establishing a relationship between the structures of the implied languages. Depending on the alignment level, t...
Eduardo Cendejas, Grettel Barceló, Alexande...
BMCBI
2011
13 years 2 months ago
Accurate statistics for local sequence alignment with position-dependent scoring by rare-event sampling
Background: Molecular database search tools need statistical models to assess the significance for the resulting hits. In the classical approach one asks the question how probable...
Stefan Wolfsheimer, Inke Herms, Sven Rahmann, Alex...