Abstract
Language detection on a very large collection of documents can be done to increasing performance of information retrieval system. One of popular method on language detection is N-Grams, based on pieces of n-characters taken from a string. This research is developed language detection system based on N-Gram that performs by Indonesian or English language. In general, the steps being taken there were 3 phases, namely creating profile of each language, system testing, and system evaluation. Fifty documents were used to creating profile of each language, i.e. 25 Indonesian and 25 English. Sixty documents were used for system testing. System performance was evaluated using F-measures. Based on the test, obtained F-measures for unigram, bigram, and unigram respectively 0.933, 0.917, and 0.933.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
