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    » Filling Knowledge Gaps in Text for Machine Reading
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    COLING
    2010
    148views Computational Linguistics» more  COLING 2010»
    Filling Knowledge Gaps in Text for Machine Reading
    13 years 5 months ago
    Filling Knowledge Gaps in Text for Machine Reading
    Download  www.aclweb.org
    Texts are replete with gaps, information omitted since authors assume a certain amount of background knowledge. We define the process of enrichment that fills these gaps. We descr...
    Anselmo Peñas, Eduard H. Hovy
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    AIED
    2009
    Springer
    113views Artificial Intelligence» more  AIED 2009»
    Interactive Paraphrase Training: The Development and Testing of an iSTART Module
    14 years 5 months ago
    Interactive Paraphrase Training: The Development and Testing of an iSTART Module
    Download  csep.psyc.memphis.edu
    Comprehension of science texts is challenging, particularly when the reader lacks the skills or knowledge necessary to fill in conceptual gaps in the text content. The iSTART syste...
    Danielle S. McNamara, Chutima Boonthum, Christophe...
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    AAAI
    2007
    101views Intelligent Agents» more  AAAI 2007»
    Learning by Reading: A Prototype System, Performance Baseline and Lessons Learned
    14 years 1 months ago
    Learning by Reading: A Prototype System, Performance Baseline and Lessons Learned
    Download  www.cs.utexas.edu
    A traditional goal of Artificial Intelligence research has been a system that can read unrestricted natural language texts on a given topic, build a model of that topic and reason...
    Ken Barker, Bhalchandra Agashe, Shaw Yi Chaw, Jame...
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    ACL
    2012
    230views Computational Linguistics» more  ACL 2012»
    Learning to "Read Between the Lines" using Bayesian Logic Programs
    12 years 1 months ago
    Learning to "Read Between the Lines" using Bayesian Logic Programs
    Download  aclweb.org
    Most information extraction (IE) systems identify facts that are explicitly stated in text. However, in natural language, some facts are implicit, and identifying them requires â€...
    Sindhu Raghavan, Raymond J. Mooney, Hyeonseo Ku
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    FLAIRS
    2009
    130views Artificial Intelligence» more  FLAIRS 2009»
    Organizing Knowledge as an Ontology of the Domain of Resilient Computing by Means of Natural Language Processing - An Experience
    13 years 8 months ago
    Organizing Knowledge as an Ontology of the Domain of Resilient Computing by Means of Natural Language Processing - An Experience
    Download  www.uni-ulm.de
    Scientists typically need to take a large volume of information into account in order to deal with re-occurring tasks such as inspecting proceedings, finding related work, or revi...
    Algirdas Avizienis, Gintare Grigonyte, Johann Hall...
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