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Polylingual Tree-Based Topic Models for Translation Domain Adaptation
Yuening Hu
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Ke Zhai
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Vladimir Eidelman
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Jordan Boyd-Graber
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Paper Details:
Month: June
Year: 2014
Location: Baltimore, Maryland
Venue:
ACL |
Citations
URL
Efficient Methods for Incorporating Knowledge into Topic Models
Yi Yang
|
Doug Downey
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Jordan Boyd-Graber
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Why ADAGRAD Fails for Online Topic Modeling
You Lu
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Jeffrey Lund
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Jordan Boyd-Graber
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Adapting Topic Models using Lexical Associations with Tree Priors
Weiwei Yang
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Jordan Boyd-Graber
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Philip Resnik
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Latent Domain Word Alignment for Heterogeneous Corpora
Hoang Cuong
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Khalil Sima’an
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Lifelong Machine Learning for Topic Modeling and Beyond
Zhiyuan Chen
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Bayesian Supervised Domain Adaptation for Short Text Similarity
Md Arafat Sultan
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Jordan Boyd-Graber
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Tamara Sumner
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Lessons from the Bible on Modern Topics: Low-Resource Multilingual Topic Model Evaluation
Shudong Hao
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Jordan Boyd-Graber
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Michael J. Paul
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A Hassle-Free Unsupervised Domain Adaptation Method Using Instance Similarity Features
Jianfei Yu
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Jing Jiang
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A Discriminative Topic Model using Document Network Structure
Weiwei Yang
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Jordan Boyd-Graber
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Philip Resnik
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Bilingual Segmented Topic Model
Akihiro Tamura
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Eiichiro Sumita
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Adapting to All Domains at Once: Rewarding Domain Invariance in SMT
Hoang Cuong
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Khalil Sima’an
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Ivan Titov
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http://www.mdbg.net/chindict/
http://www.cs.umass.edu/
Field Of Study
Task
Machine Translation
Word Segmentation
Language
Multilingual
Chinese
English
Korean
Dataset
News
Social Media
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