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    » Exploiting Syntactic Structure for Language Modeling
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    ACL
    2009
    105views Computational Linguistics» more  ACL 2009»
    Semi-supervised Learning of Dependency Parsers using Generalized Expectation Criteria
    13 years 5 months ago
    Semi-supervised Learning of Dependency Parsers using Generalized Expectation Criteria
    Download  www.cs.umass.edu
    In this paper, we propose a novel method for semi-supervised learning of nonprojective log-linear dependency parsers using directly expressed linguistic prior knowledge (e.g. a no...
    Gregory Druck, Gideon S. Mann, Andrew McCallum
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    EACL
    2009
    ACL Anthology
    123views Natural Language Processing» more  EACL 2009»
    Improving Grammaticality in Statistical Sentence Generation: Introducing a Dependency Spanning Tree Algorithm with an Argument S
    13 years 5 months ago
    Improving Grammaticality in Statistical Sentence Generation: Introducing a Dependency Spanning Tree Algorithm with an Argument S
    Download  www.aclweb.org
    like text summarisation requires a means of producing novel summary sentences. In order to improve the grammaticality of the generated sentence, we model a global (sentence) level...
    Stephen Wan, Mark Dras, Robert Dale, Cécile...
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    ACL
    2006
    160views Computational Linguistics» more  ACL 2006»
    Learning to Predict Case Markers in Japanese
    13 years 9 months ago
    Learning to Predict Case Markers in Japanese
    Download  acl.ldc.upenn.edu
    Japanese case markers, which indicate the grammatical relation of the complement NP to the predicate, often pose challenges to the generation of Japanese text, be it done by a for...
    Hisami Suzuki, Kristina Toutanova
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    ACL
    2008
    183views Computational Linguistics» more  ACL 2008»
    Exploiting Feature Hierarchy for Transfer Learning in Named Entity Recognition
    13 years 9 months ago
    Exploiting Feature Hierarchy for Transfer Learning in Named Entity Recognition
    Download  www.cs.cmu.edu
    We present a novel hierarchical prior structure for supervised transfer learning in named entity recognition, motivated by the common structure of feature spaces for this task acr...
    Andrew Arnold, Ramesh Nallapati, William W. Cohen
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    ACL
    1992
    123views Computational Linguistics» more  ACL 1992»
    GPSM: A Generalized Probabilistic Semantic Model for Ambiguity Resolution
    13 years 8 months ago
    GPSM: A Generalized Probabilistic Semantic Model for Ambiguity Resolution
    Download  nlp.csie.ncnu.edu.tw
    In natural language processing, ambiguity resolution is a central issue, and can be regarded as a preference assignment problem. In this paper, a Generalized Probabilistic Semanti...
    Jing-Shin Chang, Yih-Fen Luo, Keh-Yih Su
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