A Summariser based on Human Memory Limitations and Lexical Competition

摘要

Kintsch and van Dijk proposed a model of human comprehension and summarisation which is based on the idea of processing propositions on a sentence-by-sentence basis, detecting argument overlap, and creating a summary on the basis of the best connected propositions. We present an implementation of that model, which gets around the problem of identifying concepts in text by applying coref-erence resolution, named entity detection, and semantic similarity detection, implemented as a two-step competition. We evaluate the resulting summariser against two commonly used extractive summaris-ers using ROUGE, with encouraging results.