Abstract:
With a boom in the internet, social media text has been increasing day by day. Much of the user generated content on internet is written in a very informal way. Usually people tend to write text on social media using indigenous script. To understand a script different from ours is a difficult task. Moreover, nowadays queries received by the search engines are large number of transliterated text. Hence providing a common platform to deal with the problem of transliterated text becomes really important. This paper presents our approach to handle labeling of queries as part of the FIRE2015 shared task on Mixed-Script Information Retrieval. Tokens in the query are labeled on basis of a hybrid approach which involves rule based and machine learning techniques. Each annotation has been dealt separately but sequentially.