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1
Mark my words! Linguistic style accommodation in social media
In: http://www.cs.cornell.edu/~cristian/papers/accommodation.pdf (2011)
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2
Using mostly native data to correct errors in learners’ writing
In: http://research.microsoft.com/pubs/132140/ESLA_cameraReady_final.pdf (2010)
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3
Using Mostly Native Data to Correct Errors in Learners’ Writing: a MetaClassifier Approach. Human Language Technologies: The 2010
In: http://www.aclweb.org/anthology/N/N10/N10-1019.pdf (2010)
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4
Correcting ESL errors using phrasal smt techniques
In: http://www.mt-archive.info/Coling-ACL-2006-Brockett.pdf (2006)
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5
Correcting ESL errors using phrasal smt techniques
In: http://acl.ldc.upenn.edu/P/P06/P06-1032.pdf (2006)
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6
Sentencelevel mt evaluation without reference translations: beyond language modeling
In: http://www.mt-archive.info/EAMT-2005-Gamon.pdf (2005)
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7
2003) French Amalgam: A machine-learned sentence realization system
In: http://sites.univ-provence.fr/veronis/Atala/TALN/pdf/smets.pdf (2005)
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8
Sentence-level MT Evaluation Without Reference Translations: Beyond Language Modeling
In: http://research.microsoft.com/~anthaue/eamt05_mt_Eval.pdf (2005)
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9
Sentiment classification on customer feedback data: noisy data, large feature vectors, and the role of linguistic analysis
In: http://acl.ldc.upenn.edu/coling2004/MAIN/pdf/121-637.pdf (2005)
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10
Linguistically informed statistical models of constituent structure for ordering in sentence realization
In: http://www.aclweb.org/anthology-new/C/C04/C04-1097.pdf (2004)
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11
Linguistically informed statistical models of constituent structure for ordering in sentence realization
In: http://www.mt-archive.info/Coling-2004-Ringger.pdf (2004)
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12
Linguistic correlates of style: authorship classification with deep linguistic analysis features
In: http://research.microsoft.com/nlp/publications/coling2004_authorship.pdf (2004)
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13
Combining decision trees and transformationbased learning to correct transferred linguistic representations
In: http://www.mt-archive.info/MTS-2003-Corston.pdf (2003)
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14
Machinelearned contexts for linguistic operations in German sentence realization
In: http://research.microsoft.com/pubs/68881/acl02_mlcontext.pdf (2002)
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15
Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics (ACL), Philadelphia, July 2002, pp. 25-32. Machine-learned contexts for linguistic operations
In: http://acl.ldc.upenn.edu/P/P02/P02-1004.pdf (2002)
Abstract: We show that it is possible to learn the contexts for linguistic operations which map a semantic representation to a surface syntactic tree in sentence realization with high accuracy. We cast the problem of learning the contexts for the linguistic operations as classification tasks, and apply straightforward machine learning techniques, such as decision tree learning. The training data consist of linguistic features extracted from syntactic and semantic representations produced by a linguistic analysis system. The target features are extracted from links to surface syntax trees. Our evidence consists of four examples from the German sentence realization system code-named Amalgam: case assignment, assignment of verb position features, extraposition, and syntactic aggregation 1
URL: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.19.9028
http://acl.ldc.upenn.edu/P/P02/P02-1004.pdf
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16
Intra-sentence punctuation insertion in natural language generation
In: ftp://ftp.research.microsoft.com/pub/tr/tr-2002-58.pdf (2002)
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17
Using Machine Learning for System-Internal Evaluation of Transferred Linguistic Representations
In: http://research.microsoft.com/nlp/publications/lfeval.pdf (2001)
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18
Using Machine Learning for System-Internal Evaluation of Transferred Linguistic Representations
In: http://www.mt-archive.info/MTS-2001-Gamon.pdf (2001)
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19
Using Machine Learning for System-Internal Evaluation of Transferred Linguistic Representations
In: http://www.eamt.org/events/summitVIII/papers/gamon.pdf (2001)
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20
Practical Experience with Grammar Sharing in Multilingual NLP
In: http://acl.ldc.upenn.edu/W/W97/W97-0908.pdf (1997)
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