Identifying the Dominant Language of Web Page Using Supervised N-grams

Ng, Choon-Ching and Siau-Chuin, Liew and Wan Muhammad Syahrir, Wan Hussin and Tutut, Herawan (2013) Identifying the Dominant Language of Web Page Using Supervised N-grams. 2012 International Conference on Advanced Computer Science Applications and Technologies. pp. 344-348. (Published)

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Natural language processing is an emerging technology in linguistic industry and an aid to human-computer interaction in computer science. Language identification, on the other hand, is a form of pattern recognition that helps to identify predefined language of a web page and to predict the unknown language of one particular text. Written texts are constructed by common features such as character, word and n-gram and these characteristics are unique among languages. From the experiment result, the performance of the supervised n-gram produces an accurate identification value and outperforms the distance measurement on Arabic script web pages.

Item Type: Article
Additional Information: Liew Siaw Chuin (Siau-Chuin Liew)
Uncontrolled Keywords: Support vector machine, supervised N-grams, language identification, Arabic script
Subjects: Q Science > QA Mathematics > QA76 Computer software
Faculty/Division: Faculty of Computer System And Software Engineering
Depositing User: Ms. Hazima Anuar
Date Deposited: 09 Jan 2015 03:00
Last Modified: 27 Apr 2018 01:15
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