other,8-4-A94-1011,ak distinguishing features of a more <term> linguistically sophisticated representation </term> of <term> documents </term> over a <term>
other,8-5-A94-1011,ak leads us to consider the assignment of <term> descriptors </term> from individual <term> phrases </term>
other,8-8-A94-1011,ak statistical systems </term> can exploit <term> sophisticated representations </term> of <term> documents </term> , and lends
tech,15-3-A94-1011,ak is presented which involves using a <term> statistical POS tagger </term> in conjunction with <term> unsupervised
tech,16-2-A94-1011,ak if the power of recently developed <term> NLP techniques </term> are to be successfully applied in
tech,18-1-A94-1011,ak in performance within the standard <term> term weighting statistical assignment paradigm </term> ( Fagan 1987 ; Lewis , 1992bc ; Buckley
tech,21-3-A94-1011,ak POS tagger </term> in conjunction with <term> unsupervised structure finding methods </term> to derive notions of <term> noun group
tech,24-2-A94-1011,ak </term> are to be successfully applied in <term> IR </term> . A novel method for adding <term>
tech,26-8-A94-1011,ak sophisticated representations </term> for <term> document classification </term> . This paper reports on work done
tech,3-1-A94-1011,ak practical translation use . The use of <term> NLP techniques </term> for <term> document classification </term>
tech,4-8-A94-1011,ak representations </term> . It therefore shows that <term> statistical systems </term> can exploit <term> sophisticated representations
tech,45-3-A94-1011,ak inherently extensible to more sophisticated <term> annotation </term> , and does not require a <term> pre-tagged
tech,5-3-A94-1011,ak </term> . A novel method for adding <term> linguistic annotation </term> to <term> corpora </term> is presented
tech,6-1-A94-1011,ak use of <term> NLP techniques </term> for <term> document classification </term> has not produced significant improvements
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