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    ACL
    2009
    181views Computational Linguistics» more  ACL 2009»
    A Framework of Feature Selection Methods for Text Categorization
    13 years 8 months ago
    A Framework of Feature Selection Methods for Text Categorization
    Download  www.aclweb.org
    In text categorization, feature selection (FS) is a strategy that aims at making text classifiers more efficient and accurate. However, when dealing with a new task, it is still d...
    Shoushan Li, Rui Xia, Chengqing Zong, Chu-Ren Huan...
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    ACL
    2009
    165views Computational Linguistics» more  ACL 2009»
    Stochastic Gradient Descent Training for L1-regularized Log-linear Models with Cumulative Penalty
    13 years 8 months ago
    Stochastic Gradient Descent Training for L1-regularized Log-linear Models with Cumulative Penalty
    Download  www.aclweb.org
    Stochastic gradient descent (SGD) uses approximate gradients estimated from subsets of the training data and updates the parameters in an online fashion. This learning framework i...
    Yoshimasa Tsuruoka, Jun-ichi Tsujii, Sophia Anania...
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    ACL
    2009
    99views Computational Linguistics» more  ACL 2009»
    Exploiting Heterogeneous Treebanks for Parsing
    13 years 8 months ago
    Exploiting Heterogeneous Treebanks for Parsing
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    We address the issue of using heterogeneous treebanks for parsing by breaking it down into two sub-problems, converting grammar formalisms of the treebanks to the same one, and pa...
    Zheng-Yu Niu, Haifeng Wang, Hua Wu
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    ACL
    2009
    166views Computational Linguistics» more  ACL 2009»
    Automatic Set Instance Extraction using the Web
    13 years 8 months ago
    Automatic Set Instance Extraction using the Web
    Download  www.cs.cmu.edu
    An important and well-studied problem is the production of semantic lexicons from a large corpus. In this paper, we present a system named ASIA (Automatic Set Instance Acquirer), ...
    Richard C. Wang, William W. Cohen
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    ACL
    2009
    175views Computational Linguistics» more  ACL 2009»
    Who, What, When, Where, Why? Comparing Multiple Approaches to the Cross-Lingual 5W Task
    13 years 8 months ago
    Who, What, When, Where, Why? Comparing Multiple Approaches to the Cross-Lingual 5W Task
    Download  nlp.cs.qc.cuny.edu
    Cross-lingual tasks are especially difficult due to the compounding effect of errors in language processing and errors in machine translation (MT). In this paper, we present an er...
    Kristen Parton, Kathleen McKeown, Bob Coyne, Mona ...
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