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An Empirical Study of the Behavior of Active Learning for Word Sense Disambiguation
Jinying Chen
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Andrew Schein
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Lyle Ungar
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Martha Palmer
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Paper Details:
Month: June
Year: 2006
Location: New York City, USA
Venue:
HLT |
NAACL |
Citations
URL
Multi-Criteria-Based Strategy to Stop Active Learning for Data Annotation
Jingbo Zhu
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Huizhen Wang
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Eduard Hovy
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Bringing Active Learning to Life
Ines Rehbein
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Josef Ruppenhofer
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Alexis Palmer
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Word Sense Disambiguation Using OntoNotes: An Empirical Study
Zhi Zhong
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Hwee Tou Ng
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Yee Seng Chan
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Learning a Stopping Criterion for Active Learning for Word Sense Disambiguation and Text Classification
Jingbo Zhu
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Huizhen Wang
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Eduard Hovy
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Using Language Modeling to Select Useful Annotation Data
Dmitriy Dligach
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Martha Palmer
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Domain Adaptation with Active Learning for Word Sense Disambiguation
Yee Seng Chan
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Hwee Tou Ng
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A Combination of Active Learning and Semi-supervised Learning Starting with Positive and Unlabeled Examples for Word Sense Disambiguation: An Empirical Study on Japanese Web Search Query
Makoto Imamura
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Yasuhiro Takayama
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Nobuhiro Kaji
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Masashi Toyoda
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Masaru Kitsuregawa
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Evaluating the Impact of Coder Errors on Active Learning
Ines Rehbein
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Josef Ruppenhofer
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Good Seed Makes a Good Crop: Accelerating Active Learning Using Language Modeling
Dmitriy Dligach
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Martha Palmer
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Reducing the Need for Double Annotation
Dmitriy Dligach
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Martha Palmer
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Judging the Quality of Automatically Generated Gap-fill Question using Active Learning
Nobal Bikram Niraula
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Vasile Rus
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Experiments on Active Learning for Croatian Word Sense Disambiguation
Domagoj Alagić
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Jan Šnajder
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An Approach to Collective Entity Linking
Ashish Kulkarni
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Kanika Agarwal
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Pararth Shah
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Sunny Raj Rathod
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Ganesh Ramakrishnan
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http://www.senseval.org
http://www.cs
Field Of Study
Linguistic Trends
Discourse
Task
Tagging
Word Sense Disambiguation
Named Entity Recognition
Information Extraction
Language
English
Japanese
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