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Hits 1 – 17 of 17

1
Classifying Bias in Large Multilingual Corpora via Crowdsourcing and Topic Modeling
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2
Correcting Errors in Digital Lexicographic Resources Using a Dictionary Manipulation Language ...
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3
A random forest system combination approach for error detection in digital dictionaries ...
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4
Detecting Structural Irregularity in Electronic Dictionaries Using Language Modeling ...
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5
A random forest system combination approach for error detection in digital dictionaries
Rodrigues, Paul; Zajic, David; Doermann, David. - : Association for Computational Linguistics, 2012
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6
Citation Handling: Processing Citation Texts in Scientific Documents
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7
Detecting Structural Irregularity in Electronic Dictionaries Using Language Modeling
In: Electronic lexicography in the 21st Century: New Applications for New Users. Proceedings of eLex2011, Bled, Slowenien, 10 - 12 November 2011 (2011), 227-232
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8
Correcting Errors in Digital Lexicographic Resources Using a Dictionary Manipulation Language
In: Electronic lexicography in the 21st Century: New Applications for New Users. Proceedings of eLex2011, Bled, Slowenien, 10 - 12 November 2011 (2011), 297-301
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9
Correcting Errors in Digital Lexicographic Resources Using a Dictionary Manipulation Language ...
Zajic, David; Maxwell, Michael; Doermann, David. - : Digital Repository at the University of Maryland, 2011
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10
Detecting Structural Irregularity in Electronic Dictionaries Using Language Modeling ...
Rodrigues, Paul; Zajic, David; Doermann, David. - : Digital Repository at the University of Maryland, 2011
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11
Correcting Errors in Digital Lexicographic Resources Using a Dictionary Manipulation Language
Zajic, David; Maxwell, Michael; Doermann, David. - : Trojina Institute for Applied Slovene Studies, 2011
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12
Detecting Structural Irregularity in Electronic Dictionaries Using Language Modeling
Bloodgood, Michael; Ye, Peng; Rodrigues, Paul. - : Trojina Institute for Applied Slovene Studies, 2011
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13
Citation Handling for Improved Summarization of Scientific Documents
Abstract: In this paper we present the first steps toward improving summarization of scientific documents through citation analysis and parsing. Prior work (Mohammad et al., 2009) argues that citation texts (sentences that cite other papers) play a crucial role in automatic summarization of a topical area, but did not take into account the noise introduced by the citations themselves. We demonstrate that it is possible to improve summarization output through careful handling of these citations. We base our experiments on the application of an improved trimming approach to summarization of citation texts extracted from Question-Answering and Dependency-Parsing documents. We demonstrate that confidence scores from the Stanford NLP Parser (Klein and Manning, 2003) are significantly improved, and that Trimmer (Zajic et al., 2007), a sentence-compression tool, is able to generate higher-quality candidates. Our summarization output is currently used as part of a larger system, Action Science Explorer (ASE) (Gove, 2011).
URL: http://hdl.handle.net/1903/11822
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14
Error Correction for Arabic Dictionary Lookup
In: Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC 2010), Valetta, 17 - 23 May 2010 (2010), 263-268
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15
Multiple Alternative Sentene Compressions as a Tool for Automatic Summarization Tasks
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16
Headline Generation for Written and Broadcast News
In: DTIC (2005)
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17
Hedge Trimmer: A Parse-and-Trim Approach to Headline Generation
In: DTIC (2003)
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