To text summarization by dynamic graph mining

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Type Article in Proceedings
Conference ITAT 2018 Proceedings,
MU Faculty or unit

Faculty of Informatics

Keywords text summarization; dynamic graph mining
Description We show that frequent patterns can contribute to the quality of text summarization. Here we focus on single-document extractive summarization in English. Performance of the frequent patterns based model obtained with DGRMiner yields the most relevant sentences of all compared methods. Two out of three proposed methods outperform other methods if compared on ROUGE data.
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