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Resolving XML Semantic Ambiguity
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In: Proceedings of the 18th International Conference on Extending Database Technology, EDBT 2015, Brussels, Belgium, March 23-27, 2015. ; 18th International Conference on Extending Database Technology, EDBT 2015 ; https://hal-univ-pau.archives-ouvertes.fr/hal-01909107 ; 18th International Conference on Extending Database Technology, EDBT 2015, Mar 2015, Brussels, Belgium. pp.277-288, ⟨10.5441/002/edbt.2015.25⟩ (2015)
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| 2 |
Ten Years of Rich Internet Applications: A Systematic Mapping Study, and Beyond
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| 3 |
Textual Analysis of Stock Market Prediction Using Financial News Articles
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In: http://www.robschumaker.com/publications/ACM TOIS - Textual Analysis of Stock Market Prediction Using Financial News Articles.pdf (2006)
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Decentralizing a global naming service for improved performance and fault tolerance
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In: http://www-db.stanford.edu/~manku/quals/zpapers/89-naming.pdf.gz (1989)
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| 5 |
Analysis and Tracking of Emotions in English and Bengali Texts: A Computational Approach
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In: http://www.www2011india.com/proceeding/companion/p343.pdf
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| 6 |
Designing Delay Tolerant Applications for Low Bandwidth and Intermittently Connected Users: the aAQUA Experience
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In: http://www.it.iitb.ac.in/research/techreport/reports/43.pdf
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| 7 |
What You See is What You Worry About: Errors – Real and Imagined
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In: http://www.bcs.org//upload/pdf/ewic_hc08_v2_paper19.pdf
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Abstract:
This paper describes a text task in which children wrote their own stories in their regular school books, copied these stories onto digital paper using digital pens, had their handwritten stories recognized by the computer software, and then, looked at the text presented back to them and highlighted errors. There was considerable variability in the ability of the children to spot errors. Some children marked text as being wrong when in fact it was right. Most children spotted almost all the errors but were less likely to notice errors where incorrect but reasonable words had been presented back to them than where the words given by the recognizer were nonsense. In 13 instances, children had one of their own errors corrected by the interface but this was not noticed. The study highlighted several difficulties with the classification and reporting of errors in handwriting recognition based interfaces especially in the counting and classification of errors. Two new metrics for classifying and counting errors in this context are therefore proposed in this paper.
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Keyword:
Design; Errors; Experimentation; Handwriting recognition; Human Factors; Keywords Children; Measurement; Performance; Standardization; Text input; Tolerance
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URL: http://www.bcs.org//upload/pdf/ewic_hc08_v2_paper19.pdf
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.519.9185
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| 8 |
What are the Most Eye-catching and Ear-catching Features in the Video? Implications for Video Summarization
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In: http://ils.unc.edu/%7Eyaxiaos/publication/wfp0100-song.pdf
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| 9 |
Improved Word List Ordering for Text Entry on Ambiguous Keypads
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In: http://www.yorku.ca/mack/Nordichi2008-p152.pdf
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| 10 |
My Automated Conversation Helper (MACH): Helping People Improve Social Skills
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In: http://affect.media.mit.edu/pdfs/12.Hoque-ICMI-DC.pdf
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| 11 |
MCU at NTCIR: Chinese Fact Validation via SVM Context Ranking
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In: http://research.nii.ac.jp/ntcir/workshop/OnlineProceedings11/pdf/NTCIR/RITEVAL/19-NTCIR11-RITEVAL-WuY.pdf
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| 12 |
Empirical Comparison of Language Workbenches
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In: http://dsmforum.org/events/DSM13/Papers/Kelly.pdf
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| 13 |
Resolving Query Translation Ambiguity using a Decaying Co-occurrence Model and Syntactic Dependence Relations
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In: http://www.iro.umontreal.ca/~nie/Publication/gao-sigir02.pdf
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| 14 |
language
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In: http://research.microsoft.com/~jfgao/paper/sigir02.pdf
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