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1
Extracting definitions of mathematical expressions in scientific papers
In: https://kaigi.org/jsai/webprogram/2012/pdf/719.pdf (2012)
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2
Clustering comparable corpora for bilingual lexicon extraction
In: http://hal.inria.fr/docs/00/74/22/64/PDF/Li-Gaussier-Azawa-ACL_11_web.pdf (2011)
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3
Authors
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4
Influence of prosodic boundary on Japanese domain-final consonants. Paper presented at
In: http://www.assta.org/sst/2006/sst2006-139.pdf (2006)
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5
Influences of aging on taste perception and oral somatic sensation
In: http://biomedgerontology.oxfordjournals.org/content/60/1/109.full.pdf (2005)
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6
processes underlying perceptual enhancement by visual speech gestures
In: http://www.wlu.ca/documents/29123/Callan_et_alNeuroReport03.pdf (2003)
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7
Suppressing steady-state portions of speech for improving intelligibility in various reverberant environments
In: http://www.splab.net/papers/2002/2002_17.pdf (2002)
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8
Akiko Aizawa Linguistic Techniques to Improve the Performance of Automatic Text Categorization
In: http://research.nii.ac.jp/~akiko/papers/NLPRS2001Aizawa.pdf (2001)
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9
Linguistic Techniques to Improve the Performance of
In: http://www.afnlp.org/nlprs2001/pdf/0079-01.pdf (2001)
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10
Automatic Thesaurus Generation through Multiple Filtering
In: http://acl.ldc.upenn.edu/C/C00/C00-1058.pdf (2000)
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11
Automatic Thesaurus Generation through Multiple Filtering
In: http://research.nii.ac.jp/~kyo/papers/col2000.ps (2000)
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12
Corpus for Coreference Resolution on Scientific Papers
In: http://www.lrec-conf.org/proceedings/lrec2014/pdf/286_Paper.pdf
Abstract: Abstract The ever-growing number of published scientific papers prompts the need for automatic knowledge extraction to help scientists keep up with the state-of-the-art in their respective fields. To construct a good knowledge extraction system, annotated corpora in the scientific domain are required to train machine learning models. As described in this paper, we have constructed an annotated corpus for coreference resolution in multiple scientific domains, based on an existing corpus. We have modified the annotation scheme from Message Understanding Conference to better suit scientific texts. Then we applied that to the corpus. The annotated corpus is then compared with corpora in general domains in terms of distribution of resolution classes and performance of the Stanford Dcoref coreference resolver. Through these comparisons, we have demonstrated quantitatively that our manually annotated corpus differs from a general-domain corpus, which suggests deep differences between general-domain texts and scientific texts and which shows that different approaches can be made to tackle coreference resolution for general texts and scientific texts.
URL: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.1061.8732
http://www.lrec-conf.org/proceedings/lrec2014/pdf/286_Paper.pdf
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13
Current Perspectives and Future Directions in Foreign Language Teaching and Learning FOSTERING BETTER ORAL JAPANESE VIA E-LEARNING
In: http://www.paccall.org/2004/2004proceedings_papers/saita.pdf
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14
AVSP 2001 International Conference on Auditory-Visual Speech Processing NEURAL AREAS UNDERLYING THE PROCESSING OF VISUAL SPEECH INFORMATION UNDER CONDITIONS OF DEGRADED AUDITORY INFORMATION
In: http://isca-speech.org/archive_open/archive_papers/avsp01/av01_045.pdf
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15
Predicting Word Fixations in Text with a CRF Model for Capturing General Reading Strategies among Readers
In: http://aclweb.org/anthology/W/W12/W12-4905.pdf
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16
Use of XML and Relational Databases for Consistent Development and Maintenance of Lexicons and Annotated Corpora
In: http://www.lrec-conf.org/proceedings/lrec2002/pdf/191.pdf
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17
Building Japanese Predicate-argument Structure Corpus using Lexical Conceptual Structure
In: http://www.lrec-conf.org/proceedings/lrec2012/pdf/941_Paper.pdf
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18
Framework of Semantic Role Assignment based on Extended Lexical Conceptual Structure: Comparison with VerbNet and FrameNet
In: http://www.aclweb.org/anthology/E/E12/E12-1070.pdf
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19
Exploratory analysis of stylistic characteristics in Japanese Q&A communities
In: http://lexicometrica.univ-paris3.fr/jadt/jadt2010/allegati/JADT-2010-0355-0362_121-Suzuki.pdf
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20
Utilizing Semantic Equivalence Classes of Japanese Functional Expressions in Translation Rule Acquisition from Parallel Patent Sentences
In: http://www.mt-archive.info/LREC-2010-Nagasaka.pdf
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