Abstract
Today, research on automatic text summarization challenges on readability factor as one of the most important aspects of summarizers’ performance. In this paper, we present Pazesh: a language-independent graph-based approach for increasing the readability of summaries while preserving the most important content. Pazesh accomplishes this task by constructing a special path of salient sentences which passes through topic centroid sentences. The results show that Pazesh compares approvingly with previously published results on benchmark datasets.
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Mostafazadeh, N., Mirroshandel, S.A., Ghassem-Sani, G., Bakhshandeh Babarsad, O. (2011). Pazesh: A Graph-Based Approach to Increase Readability of Automatic Text Summaries. In: Butz, C., Lingras, P. (eds) Advances in Artificial Intelligence. Canadian AI 2011. Lecture Notes in Computer Science(), vol 6657. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21043-3_38
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DOI: https://doi.org/10.1007/978-3-642-21043-3_38
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