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1
Automatic identification of information quality metrics in health news stories
Ghezzi, Pietro; Evans, Roger; Lee, Joon. - : Frontiers Media, 2020
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2
The Extended Lexicon: language processing as Lexical description
Evans, Roger. - : RANLP 2011 Organising Committee, 2013
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3
Morphological complexity and unsupervised learning : validating Russian inflectional classes using high frequency data
In: Current issues in morphological theory (Amsterdam, 2012), p. 135-162
MPI für Psycholinguistik
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4
Morphological complexity and unsupervised learning: validating Russian inflectional classes using high frequency data
Evans, Roger; Brown, Dunstan. - : John Benjamins Publishing Co., 2012
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5
Nursing knowledge of hepatitis - 25 years later
MacLean, Alison; Angus, Neil J; Evans, Roger. - : Sage Publications, 2012
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6
Proceedings of UCNLG+Eval: Language Generation and Evaluation
Gatt, Albert; Striegnitz, Kristina; Belz, Anja. - : Association for Computational Linguistics, 2011
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7
Inflectional defaults and principal parts: an empirical investigation
Brown, Dunstan; Evans, Roger. - : CSLI Publications, 2010
Abstract: We describe an empirical method to explore and contrast the roles of default and principal part information in the differentiation of inflectional classes. We use an unsupervised machine learning method to classify Russian nouns into inflectional classes, first with full paradigm information, and then with particular types of information removed. When we remove default information, shared across classes, we expect there to be little effect on the classification. In contrast when we remove principal part information we expect there to be a more detrimental effect on classification performance. Our data set consists of paradigm listings of the 80 most frequent Russian nouns, generated from a formal theory which allows us to distinguish default and principal part information. Our results show that removal of forms classified as principal parts has a more detrimental effect on the classification than removal of default information. However, we also find that there are differences within the defaults and principal parts, and we suggest that these may in part be attributable to stress patterns.
Keyword: G400 Computing; Q100 Linguistics
URL: http://cslipublications.stanford.edu/HPSG/2010/brown-evans.pdf
http://eprints.brighton.ac.uk/8954/
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8
Proceedings of the 2009 Workshop on Language Generation and Summarisation (UCNLG+Sum 2009)
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9
Natural language processing in CLIME, a multilingual legal advisory system
In: Natural language engineering. - Cambridge : Cambridge University Press 14 (2008) 1, 101-132
BLLDB
OLC Linguistik
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10
Natural language processing in CLIME, a multilingual legal advisory system
Evans, Roger; Tipper, N.; Cahill, Lynne. - : Cambridge University Press, 2008
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11
Modelling control in generation
Paiva, Daniel; Weir, David; Carroll, John. - : Association for Computational Linguistics, 2007
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12
Modelling control in generation
Paiva, Daniel; Belz, Anja; Carroll, John. - : Association for Computational Linguistics, 2007
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13
A reference architecture for natural language generation systems
In: Natural language engineering. - Cambridge : Cambridge University Press 12 (2006) 1, 1-34
BLLDB
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14
A reference architecture for natural language generation systems
Mellish, C.; Scott, D.; Cahill, Lynne. - : Cambridge University Press, 2006
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15
Distinguishing affective states in weblogs
Genereux, M.; Evans, Roger. - : The AAAI Press, 2006
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16
Towards a validated model for affective classification of texts
BASE
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17
Interchanging lexical information for a multilingual dictionary
Borin, L.; Schulz, S.; Evans, Roger. - : American Medical Informatics Association, 2005
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18
Empirically-based control of natural language generation
Evans, Roger; Paiva, Daniel. - : Association for Computational Linguistics, 2005
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19
Supporting text mining for e-Science: the challenges for Grid-enabled natural language processing
Carroll, J.; Evans, Roger; Klein, E.. - : EPSRC, 2005
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20
Implementation architectures for natural language generation
In: Natural language engineering. - Cambridge : Cambridge University Press 10 (2004) 3-4, 261-282
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