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Keyphrase Based Arabic Summarizer (KPAS) (1206.5384v1)

Published 23 Jun 2012 in cs.CL and cs.AI

Abstract: This paper describes a computationally inexpensive and efficient generic summarization algorithm for Arabic texts. The algorithm belongs to extractive summarization family, which reduces the problem into representative sentences identification and extraction sub-problems. Important keyphrases of the document to be summarized are identified employing combinations of statistical and linguistic features. The sentence extraction algorithm exploits keyphrases as the primary attributes to rank a sentence. The present experimental work, demonstrates different techniques for achieving various summarization goals including: informative richness, coverage of both main and auxiliary topics, and keeping redundancy to a minimum. A scoring scheme is then adopted that balances between these summarization goals. To evaluate the resulted Arabic summaries with well-established systems, aligned English/Arabic texts are used through the experiments.

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Authors (2)
  1. Tarek El-Shishtawy (6 papers)
  2. Fatma El-Ghannam (4 papers)
Citations (20)