In this paper, we presents the results obtained by using a probabilistic summarization framework for the TAC 2009 update summarization task, which has the merits of combining the sentence generative probability and the sentence prior probability for sentence ranking systematically. Especially, each sentence of a document to be summarized is treated as a probabilistic generative model for predicting the documents. Nevertheless, the results of our first participation in the TAC evaluation seem to have room for further improvement.
['Shih-Hsiang Lin', 'Berlin Chen']
THE NTNU SUMMARIZATION SYSTEM AT TAC 2009