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Abstract : |
A useful first step m document summau-sation is the selection of a small number of 'meamngful ' sentences from a larger text Kupiec et al (1995) describe tim as a clas-mficatlon task on the basis of a corpus of technical papers with summaries written by professional abstractors, their system ldent~fies those sentences m the text which also occur in the summary, and then ac-quires a model of the 'abstract-worthiness' of a sentence as a combination of a hmlted numbel of properties of that sentence We report on a rephcatlon of thin exper-nnent with different data summaries for our documents were not written by pro-fessional abstractors, but by the authors themselves Tins produced fewer allguable sentences to tram on We use alternative 'meaningful ' sentences (selected by a hu-man judge) as training and evaluation ma-terial, because tlns has advantages for the subsequent automatic generation of more flexible abstracts We quantitatively com-pare the two hfferent strategies for training and evaluation (vm ahgnment vs human judgement), we also chscnss qualitative chf-ferences and consequences for the genera-tlon of abstracts 1, |
