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Query Labelling for Indic Languages using a hybrid approach

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dc.contributor.author Sharma, Yashvardhan
dc.date.accessioned 2023-01-02T09:53:55Z
dc.date.available 2023-01-02T09:53:55Z
dc.date.issued 2015
dc.identifier.uri https://www.semanticscholar.org/paper/Query-Labelling-for-Indic-Languages-using-a-hybrid-Bhargava-Sharma/3b4f56a72872dac761c863f02e28150765d3849c
dc.identifier.uri http://dspace.bits-pilani.ac.in:8080/xmlui/handle/123456789/8212
dc.description.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. en_US
dc.language.iso en en_US
dc.publisher CEUR en_US
dc.subject Computer Science en_US
dc.subject Transliteration en_US
dc.subject Natural Language Processing en_US
dc.subject Language Identification en_US
dc.subject Machine learning en_US
dc.subject Machine Learning en_US
dc.title Query Labelling for Indic Languages using a hybrid approach en_US
dc.type Article en_US


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