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Finding similarities between two inter-language news articles is achallenging problem of Natural Language Processing (NLP). It is difficult tofind similar news articles in a different language other than the nativelanguage of user, there is a need for a Machine Learning based automatic systemto find the similarity between two inter-language news articles. In thisarticle, we propose a Machine Learning model with the combination of EnglishUrdu word transliteration which will show whether the English news article issimilar to the Urdu news article or not. The existing approaches to findsimilarities has a major drawback when the archives contain articles oflow-resourced languages like Urdu along with English news article. The existingapproaches to find similarities has drawback when the archives containlow-resourced languages like Urdu along with English news articles. We usedlexicon to link Urdu and English news articles. As Urdu language processingapplications like machine translation, text to speech, etc are unable to handleEnglish text at the same time so this research proposed technique to findsimilarities in English and Urdu news articles based on transliteration.

Exploiting Transliterated Words for Finding Similarity in Inter-Language News Articles using Machine Learning