International Conference Recent Advances in Natural Language Processing
نویسندگان
چکیده
Part-of-Speech (POS) tagging is a key stepin many NLP algorithms. However, tweetsare difficult to POS tag because there aremany phenomena that frequently appear inTwitter that are not as common, or are en-tirely absent, in other domains: tweets areshort, are not always written maintainingformal grammar and proper spelling, andabbreviations are often used to overcometheir restricted lengths. Arabic tweets alsoshow a further range of linguistic phenom-ena such as usage of different dialects,romanised Arabic and borrowing foreignwords. In this paper, we present an evalu-ation and a detailed error analysis of state-of-the-art POS taggers for Arabic whenapplied to Arabic tweets. The accuracy ofstandard Arabic taggers is typically excel-lent (96-97%) on Modern Standard Arabic(MSA) text; however, their accuracy de-clines to 49-65% on Arabic tweets. Fur-ther, we present our initial approach to im-prove the taggers’ performance. By doingsome improvements based on observed er-rors, we are able to reach 79% tagging ac-curacy.
منابع مشابه
Word Class Functions for Syntactic-Semantic Analysis
Appeared in Proceedings of the 2nd International Conference on Recent Advances in Natural Language Processing (RANLP’97), pp. 312–317, 1997. In this paper, Analysis with Word Class Functions (WCFA) is presented as a paradigm for syntactic-semantic analysis of natural language. The main characteristics of this approach are: word-orientation, the central role of word class functions, two phases o...
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