Query Labelling for Indic Languages using a hybrid approach

dc.contributor.authorSharma, Yashvardhan
dc.date.accessioned2023-01-02T09:53:55Z
dc.date.available2023-01-02T09:53:55Z
dc.date.issued2015
dc.description.abstractWith 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.en_US
dc.identifier.urihttps://www.semanticscholar.org/paper/Query-Labelling-for-Indic-Languages-using-a-hybrid-Bhargava-Sharma/3b4f56a72872dac761c863f02e28150765d3849c
dc.identifier.urihttp://dspace.bits-pilani.ac.in:8080/xmlui/handle/123456789/8212
dc.language.isoenen_US
dc.publisherCEURen_US
dc.subjectComputer Scienceen_US
dc.subjectTransliterationen_US
dc.subjectNatural Language Processingen_US
dc.subjectLanguage Identificationen_US
dc.subjectMachine learningen_US
dc.subjectMachine Learningen_US
dc.titleQuery Labelling for Indic Languages using a hybrid approachen_US
dc.typeArticleen_US

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