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Using “Annotator Rationales” to Improve Machine Learning for Text Categorization
Omar Zaidan
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Jason Eisner
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Christine Piatko
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Paper Details:
Month: April
Year: 2007
Location: Rochester, New York
Venue:
NAACL |
Citations
URL
Learning Noun Phrase Query Segmentation
Shane Bergsma
|
Qin Iris Wang
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Multi-Level Structured Models for Document-Level Sentiment Classification
Ainur Yessenalina
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Yisong Yue
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Claire Cardie
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Why are You Taking this Stance? Identifying and Classifying Reasons in Ideological Debates
Kazi Saidul Hasan
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Vincent Ng
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Rationalizing Neural Predictions
Tao Lei
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Regina Barzilay
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Tommi Jaakkola
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Deriving Machine Attention from Human Rationales
Yujia Bao
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Shiyu Chang
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Mo Yu
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Regina Barzilay
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Recovering Traceability Links in Requirements Documents
Zeheng Li
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Mingrui Chen
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LiGuo Huang
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Vincent Ng
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Feature Selection as Causal Inference: Experiments with Text Classification
Michael J. Paul
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Interactive Annotation Learning with Indirect Feature Voting
Shilpa Arora
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Eric Nyberg
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Discourse Connectors for Latent Subjectivity in Sentiment Analysis
Rakshit Trivedi
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Jacob Eisenstein
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Active Learning with Rationales for Text Classification
Manali Sharma
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Di Zhuang
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Mustafa Bilgic
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Comparing Automatic and Human Evaluation of Local Explanations for Text Classification
Dong Nguyen
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A Study of Information Retrieval Weighting Schemes for Sentiment Analysis
Georgios Paltoglou
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Mike Thelwall
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Automatically Generating Annotator Rationales to Improve Sentiment Classification
Ainur Yessenalina
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Yejin Choi
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Claire Cardie
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Using Conceptual Class Attributes to Characterize Social Media Users
Shane Bergsma
|
Benjamin Van Durme
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Sentiment Relevance
Christian Scheible
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Hinrich Schütze
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Automating Biomedical Evidence Synthesis: RobotReviewer
Iain Marshall
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Joël Kuiper
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Edward Banner
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Byron C. Wallace
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Analysis Methods in Neural Language Processing: A Survey
Yonatan Belinkov
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James Glass
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Interactive Feature Space Construction using Semantic Information
Dan Roth
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Kevin Small
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Estimating Annotation Cost for Active Learning in a Multi-Annotator Environment
Shilpa Arora
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Eric Nyberg
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Carolyn P. Rosé
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Improved Natural Language Learning via Variance-Regularization Support Vector Machines
Shane Bergsma
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Dekang Lin
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Dale Schuurmans
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Assessing Benefit from Feature Feedback in Active Learning for Text Classification
Shilpa Arora
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Eric Nyberg
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http://cs.jhu.edu/ozaidan/rationales
Field Of Study
Task
Text Categorization
Approach
Discriminative Model
Semi-supervised Learning
Language
English
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