Abstract
This paper examines the benefits of both the Rhetorical Representation and Vector Representation for Arabic text summarization. The Rhetorical Representation uses the Rhetorical Structure Theory (RST) for building the Rhetorical Structure Tree (RS-Tree) and extracts the most significant paragraphs as a summary. On the other hand, the Vector Representation uses a cosine similarity measure for ranking and extracting the most significant paragraphs as a summary. The framework evaluates both summaries using precision. Statistical results show that Rhetorical Representation is superior to Vector Representation. Moreover, the rhetorical summary keeps the text in context, without leading to lack of cohesion in which the anaphoric reference is not broken i.e. improving the ability of extracting the semantics behind the text.
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Ibrahim, A., Elghazaly, T. (2013). Rhetorical Representation and Vector Representation in Summarizing Arabic Text. In: Métais, E., Meziane, F., Saraee, M., Sugumaran, V., Vadera, S. (eds) Natural Language Processing and Information Systems. NLDB 2013. Lecture Notes in Computer Science, vol 7934. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38824-8_53
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DOI: https://doi.org/10.1007/978-3-642-38824-8_53
Publisher Name: Springer, Berlin, Heidelberg
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