  In this paper we introduce a dynamic programming algorithm to perform linear
text segmentation by global minimization of a segmentation cost function which
consists of: (a) within-segment word similarity and (b) prior information about
segment length. The evaluation of the segmentation accuracy of the algorithm on
a text collection consisting of Greek texts showed that the algorithm achieves
high segmentation accuracy and appears to be very innovating and promissing.
