Multi-document Summarization Using Minimum Distortion

Document summarization plays an important role in the area of natural language processing and text mining. This paper proposes several novel information-theoretic models for multi-document summarization. They consider document summarization as a transmission system and assume that the best summary should have the minimum distortion. By defining a proper distortion measure and a new representation method, the combination of the last two models (the linear representation model and the facility location model) gains good experimental results on the DUC2002 and DUC2004 datasets. Moreover, we also indicate that the model has high interpretability and extensibility.

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