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Query A94-1011 36 >
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tech,21-3-A94-1011,bq	POS tagger </term> in conjunction with <term>	unsupervised structure finding methods	</term> to derive notions of <term> noun group	#19966 A novel method for adding linguistic annotation to corpora is presented which involves using a statistical POS tagger in conjunction withunsupervised structure finding methods to derive notions of noun group, verb group, and so on which is inherently extensible to more sophisticated annotation, and does not require a pre-tagged corpus to fit.
other,7-6-A94-1011,bq	sets of individually high-precision <term>	rules	</term> can result in a <term> low precision	#20076 We investigate how sets of individually high-precisionrules can result in a low precision when used together, and develop some theory about these probably-correct rules.
other,8-8-A94-1011,bq	statistical systems </term> can exploit <term>	sophisticated representations of documents	</term> , and lends some support to the use	#20142 It therefore shows that statistical systems can exploitsophisticated representations of documents, and lends some support to the use of more linguistically sophisticated representations for document classification.
tech,16-2-A94-1011,bq	if the power of recently developed <term>	NLP techniques	</term> are to be successfully applied in	#19935 This perplexing fact needs both an explanation and a solution if the power of recently developedNLP techniques are to be successfully applied in IR.
other,26-9-A94-1011,bq	based tool </term> to be used in the <term>	technical abstracting industry	</term> . This paper proposes a model using	#20189 This paper reports on work done for the LRE project SmTA double check, which is creating a PC based tool to be used in thetechnical abstracting industry.
tech,18-9-A94-1011,bq	check </term> , which is creating a <term>	PC based tool	</term> to be used in the <term> technical	#20181 This paper reports on work done for the LRE project SmTA double check, which is creating aPC based tool to be used in the technical abstracting industry.
tech,26-7-A94-1011,bq	representations </term> , and show that a <term>	statistically fitted rule-based model	</term> provides significantly improved performance	#20122 We then proceed to repeat results which show that standard statistical models are not particularly suitable for exploiting linguistically sophisticated representations, and show that astatistically fitted rule-based model provides significantly improved performance for sophisticated representations.
other,45-3-A94-1011,bq	inherently extensible to more sophisticated <term>	annotation	</term> , and does not require a <term> pre-tagged	#19990 A novel method for adding linguistic annotation to corpora is presented which involves using a statistical POS tagger in conjunction with unsupervised structure finding methods to derive notions of noun group, verb group, and so on which is inherently extensible to more sophisticatedannotation, and does not require a pre-tagged corpus to fit.
other,5-3-A94-1011,bq	</term> . A novel method for adding <term>	linguistic annotation	</term> to <term> corpora </term> is presented	#19950 A novel method for addinglinguistic annotation to corpora is presented which involves using a statistical POS tagger in conjunction with unsupervised structure finding methods to derive notions of noun group, verb group, and so on which is inherently extensible to more sophisticated annotation, and does not require a pre-tagged corpus to fit.
other,29-3-A94-1011,bq	methods </term> to derive notions of <term>	noun group	</term> , <term> verb group </term> , and so	#19974 A novel method for adding linguistic annotation to corpora is presented which involves using a statistical POS tagger in conjunction with unsupervised structure finding methods to derive notions ofnoun group, verb group, and so on which is inherently extensible to more sophisticated annotation, and does not require a pre-tagged corpus to fit.
other,8-4-A94-1011,bq	distinguishing features of a more <term>	linguistically sophisticated representation of documents	</term> over a <term> word set based representation	#20010 One of the distinguishing features of a morelinguistically sophisticated representation of documents over a word set based representation of them is that linguistically sophisticated units are more frequently individually good predictors of document descriptors (keywords) than single words are.
other,40-4-A94-1011,bq	descriptors ( keywords ) </term> than single <term>	words	</term> are . This leads us to consider the	#20042 One of the distinguishing features of a more linguistically sophisticated representation of documents over a word set based representation of them is that linguistically sophisticated units are more frequently individually good predictors of document descriptors (keywords) than singlewords are.
tech,4-8-A94-1011,bq	representations </term> . It therefore shows that <term>	statistical systems	</term> can exploit <term> sophisticated representations	#20138 It therefore shows thatstatistical systems can exploit sophisticated representations of documents, and lends some support to the use of more linguistically sophisticated representations for document classification.
lr,8-3-A94-1011,bq	<term> linguistic annotation </term> to <term>	corpora	</term> is presented which involves using	#19953 A novel method for adding linguistic annotation tocorpora is presented which involves using a statistical POS tagger in conjunction with unsupervised structure finding methods to derive notions of noun group, verb group, and so on which is inherently extensible to more sophisticated annotation, and does not require a pre-tagged corpus to fit.
other,11-5-A94-1011,bq	<term> descriptors </term> from individual <term>	phrases	</term> rather than from the <term> weighted	#20056 This leads us to consider the assignment of descriptors from individualphrases rather than from the weighted sum of a word set representation.
tech,18-1-A94-1011,bq	in performance within the standard <term>	term weighting statistical assignment paradigm	</term> ( Fagan 1987 ; Lewis , 1992bc ; Buckley	#19901 The use of NLP techniques for document classification has not produced significant improvements in performance within the standardterm weighting statistical assignment paradigm (Fagan 1987; Lewis, 1992bc; Buckley, 1993).
tech,15-3-A94-1011,bq	is presented which involves using a <term>	statistical POS tagger	</term> in conjunction with <term> unsupervised	#19960 A novel method for adding linguistic annotation to corpora is presented which involves using astatistical POS tagger in conjunction with unsupervised structure finding methods to derive notions of noun group, verb group, and so on which is inherently extensible to more sophisticated annotation, and does not require a pre-tagged corpus to fit.
other,20-5-A94-1011,bq	from the <term> weighted sum </term> of a <term>	word set representation	</term> . We investigate how sets of individually	#20065 This leads us to consider the assignment of descriptors from individual phrases rather than from the weighted sum of aword set representation.
other,32-3-A94-1011,bq	notions of <term> noun group </term> , <term>	verb group	</term> , and so on which is inherently extensible	#19977 A novel method for adding linguistic annotation to corpora is presented which involves using a statistical POS tagger in conjunction with unsupervised structure finding methods to derive notions of noun group,verb group, and so on which is inherently extensible to more sophisticated annotation, and does not require a pre-tagged corpus to fit.
other,8-9-A94-1011,bq	paper reports on work done for the <term>	LRE project SmTA double check	</term> , which is creating a <term> PC based	#20171 This paper reports on work done for theLRE project SmTA double check, which is creating a PC based tool to be used in the technical abstracting industry.


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