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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; Zajic, David; Doermann, David. - : Trojina Institute for Applied Slovene Studies, 2011
Abstract: Dictionaries are often developed using tools that save to Extensible Markup Language (XML)-based standards. These standards often allow high-level repeating elements to represent lexical entries, and utilize descendants of these repeating elements to represent the structure within each lexical entry, in the form of an XML tree. In many cases, dictionaries are published that have errors and inconsistencies that are expensive to find manually. This paper discusses a method for dictionary writers to quickly audit structural regularity across entries in a dictionary by using statistical language modeling. The approach learns the patterns of XML nodes that could occur within an XML tree, and then calculates the probability of each XML tree in the dictionary against these patterns to look for entries that diverge from the norm. ; This material is based upon work supported, in whole or in part, with funding from the United States Government. Any opinions, findings and conclusions, or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the University of Maryland, College Park and/or any agency or entity of the United States Government. Nothing in this report is intended to be and shall not be treated or construed as an endorsement or recommendation by the University of Maryland, United States Government, or the authors of the product, process, or service that is the subject of this report. No one may use any information contained or based on this report in advertisements or promotional materials related to any company product, process, or service or in support of other commercial purposes.
Keyword: anomaly detection; computational linguistics; computer science; electronic dictionaries; electronic lexicography; error correction; human language technology; language modeling; natural language processing; statistical methods; XML
URL: https://doi.org/10.13016/M2WC75
http://hdl.handle.net/1903/15576
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13
Citation Handling for Improved Summarization of Scientific Documents
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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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