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    EACL
    2006
    ACL Anthology
    84views Natural Language Processing» more  EACL 2006»
    Example-Based Metonymy Recognition for Proper Nouns
    13 years 9 months ago
    Example-Based Metonymy Recognition for Proper Nouns
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    Metonymy recognition is generally approached with complex algorithms that rely heavily on the manual annotation of training and test data. This paper will relieve this complexity ...
    Yves Peirsman
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    EACL
    2006
    ACL Anthology
    148views Natural Language Processing» more  EACL 2006»
    Word Sense Induction: Triplet-Based Clustering and Automatic Evaluation
    13 years 9 months ago
    Word Sense Induction: Triplet-Based Clustering and Automatic Evaluation
    Download  acl.ldc.upenn.edu
    In this paper a novel solution to automatic and unsupervised word sense induction (WSI) is introduced. It represents an instantiation of the `one sense per collocation' obser...
    Stefan Bordag
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    EACL
    2006
    ACL Anthology
    131views Natural Language Processing» more  EACL 2006»
    Making Tree Kernels Practical for Natural Language Learning
    13 years 9 months ago
    Making Tree Kernels Practical for Natural Language Learning
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    In recent years tree kernels have been proposed for the automatic learning of natural language applications. Unfortunately, they show (a) an inherent super linear complexity and (...
    Alessandro Moschitti
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    EACL
    2006
    ACL Anthology
    151views Natural Language Processing» more  EACL 2006»
    Improving Probabilistic Latent Semantic Analysis with Principal Component Analysis
    13 years 9 months ago
    Improving Probabilistic Latent Semantic Analysis with Principal Component Analysis
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    Probabilistic Latent Semantic Analysis (PLSA) models have been shown to provide a better model for capturing polysemy and synonymy than Latent Semantic Analysis (LSA). However, th...
    Ayman Farahat, Francine Chen
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    EACL
    2006
    ACL Anthology
    143views Natural Language Processing» more  EACL 2006»
    Using Reinforcement Learning to Build a Better Model of Dialogue State
    13 years 9 months ago
    Using Reinforcement Learning to Build a Better Model of Dialogue State
    Download  acl.ldc.upenn.edu
    Given the growing complexity of tasks that spoken dialogue systems are trying to handle, Reinforcement Learning (RL) has been increasingly used as a way of automatically learning ...
    Joel R. Tetreault, Diane J. Litman
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