Revisiting the Centroid-based Method: A Strong Baseline for Multi-Document Summarization

Demian Gholipour Ghalandari

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arXiv · 1708.07690

Revisiting the Centroid-based Method: A Strong Baseline for Multi-Document Summarization

Demian Gholipour Ghalandari

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Abstract

The centroid-based model for extractive document summarization is a simple and fast baseline that ranks sentences based on their similarity to a centroid vector. In this paper, we apply this ranking to possible summaries instead of sentences and use a simple greedy algorithm to find the best summary. Furthermore, we show possi- bilities to scale up to larger input docu- ment collections by selecting a small num- ber of sentences from each document prior to constructing the summary. Experiments were done on the DUC2004 dataset for multi-document summarization. We ob- serve a higher performance over the orig- inal model, on par with more complex state-of-the-art methods.

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Demian Gholipour Ghalandari. 2017-08-25. Revisiting the Centroid-based Method: A Strong Baseline for Multi-Document Summarization. https://arxiv.org/abs/1708.07690

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