Automatic selection of the subject sentences from abstracts bearing
Takashi Harada, Hiroshi Maruyama, Motomi Satoh, Kimio Hosono, Masayuki Morohashi · Library and Information Science · 1992
In order to automatically extract good free keywords for content designation from any kind of text, it must be effective and efficient to single out subject bearing sentences at first, and then extract those keywords from them.This paper, first of all, describes characteristics of a method developed to automatically discriminate such sentences from those which show premises and conclusions, based on the relative position of the sentences in texts and the paticular expressions appeared in them.Then this paper reports that the result of the experiment where the method was applied to the abstracts in the field of computer science. In 286 out of 386 abstracts (69.4%), almost all sentences include in them were classified successfully. Furtheremore, some of the sentences were recognized conectly in 65 abstracts. As far as the first sentence is a subject bearing one, it was identified so with very high probability i.e. 97.1%.