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108
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ACL
2009
14 years 10 months ago
Semi-Supervised Active Learning for Sequence Labeling
While Active Learning (AL) has already been shown to markedly reduce the annotation efforts for many sequence labeling tasks compared to random selection, AL remains unconcerned a...
Katrin Tomanek, Udo Hahn
94
Voted
ACL
2010
14 years 10 months ago
Learning Lexicalized Reordering Models from Reordering Graphs
Lexicalized reordering models play a crucial role in phrase-based translation systems. They are usually learned from the word-aligned bilingual corpus by examining the reordering ...
Jinsong Su, Yang Liu, Yajuan Lü, Haitao Mi, Q...
106
Voted
IJCNLP
2004
Springer
15 years 6 months ago
Combining Labeled and Unlabeled Data for Learning Cross-Document Structural Relationships
Multi-document discourse analysis has emerged with the potential of improving various NLP applications. Based on the newly proposed Cross-document Structure Theory (CST), this pap...
Zhu Zhang, Dragomir R. Radev
NAACL
2004
15 years 2 months ago
Detecting Structural Metadata with Decision Trees and Transformation-Based Learning
The regular occurrence of disfluencies is a distinguishing characteristic of spontaneous speech. Detecting and removing such disfluencies can substantially improve the usefulness ...
Joungbum Kim, Sarah E. Schwarm, Mari Ostendorf
105
Voted
COLING
1996
15 years 2 months ago
FeasPar - A Feature Structure Parser Learning to Parse Spoken Language
We describe and experimentally evaluate a system, FeasPar, that learns parsing spontaneous speech. To train and run FeasPar (Feature Structure Parser), only limited handmodeled kn...
Finn Dag Buø, Alex Waibel