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arXiv · 1606.03143

PerSum: Novel Systems for Document Summarization in Persian

Saeid Parvandeh·Shibamouli Lahiri·Fahimeh Boroumand
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Abstract

In this paper we explore the problem of document summarization in Persian language from two distinct angles. In our first approach, we modify a popular and widely cited Persian document summarization framework to see how it works on a realistic corpus of news articles. Human evaluation on generated summaries shows that graph-based methods perform better than the modified systems. We carry this intuition forward in our second approach, and probe deeper into the nature of graph-based systems by designing several summarizers based on centrality measures. Ad hoc evaluation using ROUGE score on these summarizers suggests that there is a small class of centrality measures that perform better than three strong unsupervised baselines.

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Saeid Parvandeh, Shibamouli Lahiri, Fahimeh Boroumand. 2016-06-09. PerSum: Novel Systems for Document Summarization in Persian. https://arxiv.org/abs/1606.03143

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