Morpheme matching based text tokenization for a scarce resourced language.

Morpheme matching based text tokenization for a scarce resourced language.

Blog Article

Text tokenization is a fundamental pre-processing step for almost all the information processing applications.This task Ginkgo Biloba is nontrivial for the scarce resourced languages such as Urdu, as there is inconsistent use of space between words.In this paper a morpheme matching based approach has been proposed for Urdu text tokenization, along with some other algorithms to Reachers solve the additional issues of boundary detection of compound words, affixation, reduplication, names and abbreviations.

This study resulted into 97.28% precision, 93.71% recall, and 95.

46% F1-measure; while tokenizing a corpus of 57000 words by using a morpheme list with 6400 entries.