A00-1002 domain-related glossary in an off-line preprocessing stage , which does not require
A00-1033 were caused by mistakes in the preprocessing phase . For example ten errors
A00-1022 slightly varied with the kind of preprocessing used . During the learning phase
A88-1013 problem with our free-form text by preprocessing all new text to find new words
A00-1022 they have passed the linguistic preprocessing . The resulting category is in
A00-1022 achieved with different linguistic preprocessing and learning algorithms and provide
A88-1014 dictionary entries . Considerable preprocessing was necessary in order to prepare
A00-1009 by the next module . As for the preprocessing rules , these rules can be used
A00-1022 occurrence of new top - ics . Thus the preprocessing results will often differ for
A00-1022 Shallow Text Processing Linguistic preprocessing of text documents is carried
A88-1032 information ) , and some simplifying preprocessing is done . Each of the flattened
A00-1022 different methods of STP-based preprocessing . Section 4 describes the results
A00-2019 Once a target word is chosen , preprocessing , building a model of the word
A83-1029 process - ing , terminology aids , preprocessing aids and a link to an off-line
A88-1014 Analysis of Definitions 3.1 . Preprocessing for the parser The definition
A00-1004 have to undergo a series of some preprocessing , which , to some extent , is
A00-1022 Would more extensive linguistic preprocessing help ? Other tests not reported
A00-2036 parsing , requiring polynomial-time preprocessing of the grammar , also can not
A00-1022 RIPPER and SVM_Light , linguistic preprocessing increased the overall performance
A83-1029 and two additional aids -- ( a ) preprocessing of the source text to search
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