Using Synchronic and Diachronic Relations for Summarizing Multiple Documents Describing Evolving Events

TL;DR

This paper introduces a novel methodology using Synchronic and Diachronic Relations to automatically summarize evolving events from multiple sources, effectively capturing similarities and differences over time.

Contribution

It presents a new approach based on SDRs and message structures for summarizing both linear and non-linear evolving events from multiple documents.

Findings

Effective summarization of football match events.

Successful summarization of terrorist incident reports.

The methodology produces coherent, informative summaries.

Abstract

In this paper we present a fresh look at the problem of summarizing evolving events from multiple sources. After a discussion concerning the nature of evolving events we introduce a distinction between linearly and non-linearly evolving events. We present then a general methodology for the automatic creation of summaries from evolving events. At its heart lie the notions of Synchronic and Diachronic cross-document Relations (SDRs), whose aim is the identification of similarities and differences between sources, from a synchronical and diachronical perspective. SDRs do not connect documents or textual elements found therein, but structures one might call messages. Applying this methodology will yield a set of messages and relations, SDRs, connecting them, that is a graph which we call grid. We will show how such a grid can be considered as the starting point of a Natural Language Generation System. The methodology is evaluated in two case-studies, one for linearly evolving events (descriptions of football matches) and another one for non-linearly evolving events (terrorist incidents involving hostages). In both cases we evaluate the results produced by our computational systems.