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    COGSCI
    2010
    62views more  COGSCI 2010»
    Exploiting Multiple Sources of Information in Learning an Artificial Language: Human Data and Modeling
    13 years 2 months ago
    Exploiting Multiple Sources of Information in Learning an Artificial Language: Human Data and Modeling
    Download  leadserv.u-bourgogne.fr
    Pierre Perruchet, Barbara Tillmann
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    AAAI
    1996
    159views Intelligent Agents» more  AAAI 1996»
    Learning Models for Multi-Source Integration
    13 years 6 months ago
    Learning Models for Multi-Source Integration
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    One issue involved in accessing multiple heterogeneous information sources is how to integrate the retrieved data. SIMS, an information mediator, handles this problem by mapping t...
    Sheila Tejada, Craig A. Knoblock, Steven Minton
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    ACL
    2008
    101views Computational Linguistics» more  ACL 2008»
    Unsupervised Multilingual Learning for Morphological Segmentation
    13 years 6 months ago
    Unsupervised Multilingual Learning for Morphological Segmentation
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    For centuries, the deep connection between languages has brought about major discoveries about human communication. In this paper we investigate how this powerful source of inform...
    Benjamin Snyder, Regina Barzilay
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    ACL
    2004
    122views Computational Linguistics» more  ACL 2004»
    The Sentimental Factor: Improving Review Classification Via Human-Provided Information
    13 years 6 months ago
    The Sentimental Factor: Improving Review Classification Via Human-Provided Information
    Download  acl.ldc.upenn.edu
    Sentiment classification is the task of labeling a review document according to the polarity of its prevailing opinion (favorable or unfavorable). In approaching this problem, a m...
    Philip Beineke, Trevor Hastie, Shivakumar Vaithyan...
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    ACL
    2008
    183views Computational Linguistics» more  ACL 2008»
    Exploiting Feature Hierarchy for Transfer Learning in Named Entity Recognition
    13 years 6 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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