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Linear Evolving Summarization: The First Results

We examine a method for the creation of multi-document evolving summaries, i.e. summaries of events that evolve through time. We distinguish such summaries into linear and non-linear. In this paper we focus in summaries that evolve linearly. In order to tackle the problem we introduce the notion of cross-document relations which connect some simple structures, which we call messages, in two exes: synchronically and diachronically. Apart from the theoretic background we provide, we also report on several Machine Learning experiments that we performed in order to automatically extract the messages and the synchronic and diachronic relations that connect them.