Modeling Classifier for Code Mixed Cross Script Questions

Abstract

With a boom in the internet, the social media text had been increasing day by day and the user generated content (such as tweets and blogs) in Indian languages are written using Roman script due to various socio-cultural and technological reasons. A majority of these posts are multilingual in nature and many involve code mixing where lexical items and gram- matical features from two languages appear in one sentence. Focusing on this current multilingual scenario, code-mixed cross-script (i.e., non-native script) data gives rise to a new problem and presents serious challenges to automatic Ques- tion Answering (QA) and for this question classi cation will be required which is an important step towards QA. This paper proposes an approach to handle cross script question classi cation as it is an important task of question analysis which detects the category of the question.