2004 AutomaticTaggingofArabicTextFro

• (Diab et al., 2004) ⇒ Mona Diab, Kadri Hacioglu, and Daniel Jurafsky. (2004). “ Automatic Tagging of Arabic Text: From Raw Text to Base Phrase Chunks". In: Proceedings of HLT-NAACL 2004: Short Papers. ISBN:1-932432-24-8

Subject Headings: Morphological Analysis Task, Morphological Parsing Task.

Cited By

• http://scholar.google.com/scholar?q=%222004%22+Automatic+Tagging+of+Arabic+Text%3A+From+Raw+Text+to+Base+Phrase+Chunks
• http://dl.acm.org/citation.cfm?id=1613984.1614022&preflayout=flat#citedby

Quotes

Abstract

To date, there are no fully automated systems addressing the community's need forfundamental language processing tools for Arabic text. In this paper, we present a Support Vector Machine (SVM) based approach to automatically tokenize (segmenting off clitics), part-of-speech (POS) tag and annotate base phrases (BPs) in Arabic text. We adapt highly accurate tools that have been developed for English text and apply them to Arabic text. Using standard evaluation metrics, we report that the SVM-TOK tokenizer achieves an F_β=1 score of 99.12, the SVM-POS tagger achieves an accuracy of 95.49%, and the SVM-BP chunker yields an F_β=1 score of 92.08.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2004 AutomaticTaggingofArabicTextFro	Daniel Jurafsky Mona Diab Kadri Hacioglu			Automatic Tagging of Arabic Text: From Raw Text to Base Phrase Chunks						2004