A neural network-based automatic summarization for the minutes of local assemblies

An automatic summarization system for local assembly minutes is described. Our system is unique in the following two points: First, the completeness that puts emphasis on the readability of the generated summary is realized. Secondly, the preference that prioritizes the selection based on the viewpoint on the content of the summary is considered. Our system has a t wo-level structure that brings about the property of "anytime algorithm": The neural network in the lower layer recollects important sentences based on the frequency of the words in the text. Then, based on the snapshot of the neural network, the summary gnerator in the upper layer extracts a cluster of sentences around the important sentences, with the prioritization by the user's preferred viewpoint. The effectiveness of our method is demonstrated using the actual minutes of a prefecture in Japan.