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    JMLR
    2012
    220views Programming Languages» more  JMLR 2012»
    Joint Learning of Words and Meaning Representations for Open-Text Semantic Parsing
    12 years 9 days ago
    Joint Learning of Words and Meaning Representations for Open-Text Semantic Parsing
    Download  jmlr.csail.mit.edu
    Open-text semantic parsers are designed to interpret any statement in natural language by inferring a corresponding meaning representation (MR – a formal representation of its s...
    Antoine Bordes, Xavier Glorot, Jason Weston, Yoshu...
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    EMNLP
    2008
    105views Natural Language Processing» more  EMNLP 2008»
    Learning Graph Walk Based Similarity Measures for Parsed Text
    13 years 11 months ago
    Learning Graph Walk Based Similarity Measures for Parsed Text
    Download  www.cs.cmu.edu
    We consider a parsed text corpus as an instance of a labelled directed graph, where nodes represent words and weighted directed edges represent the syntactic relations between the...
    Einat Minkov, William W. Cohen
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    COLING
    1996
    92views Computational Linguistics» more  COLING 1996»
    FeasPar - A Feature Structure Parser Learning to Parse Spoken Language
    13 years 11 months ago
    FeasPar - A Feature Structure Parser Learning to Parse Spoken Language
    Download  acl.ldc.upenn.edu
    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
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    NAACL
    2004
    92views Computational Linguistics» more  NAACL 2004»
    Ensemble-based Active Learning for Parse Selection
    13 years 11 months ago
    Ensemble-based Active Learning for Parse Selection
    Download  acl.ldc.upenn.edu
    Supervised estimation methods are widely seen as being superior to semi and fully unsupervised methods. However, supervised methods crucially rely upon training sets that need to ...
    Miles Osborne, Jason Baldridge
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    ACL
    2010
    149views Computational Linguistics» more  ACL 2010»
    Hierarchical Joint Learning: Improving Joint Parsing and Named Entity Recognition with Non-Jointly Labeled Data
    13 years 7 months ago
    Hierarchical Joint Learning: Improving Joint Parsing and Named Entity Recognition with Non-Jointly Labeled Data
    Download  www-nlp.stanford.edu
    One of the main obstacles to producing high quality joint models is the lack of jointly annotated data. Joint modeling of multiple natural language processing tasks outperforms si...
    Jenny Rose Finkel, Christopher D. Manning
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