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vol.20 issue3Follower Behavior Analysis via Influential Transmitters on Social Issues in TwitterUsing Word Embeddings for Query Translation for Hindi to English Cross Language Information Retrieval author indexsubject indexsearch form
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Computación y Sistemas

On-line version ISSN 2007-9737Print version ISSN 1405-5546

Abstract

CHAKMA, Kunal  and  DAS, Amitava. CMIR: A Corpus for Evaluation of Code Mixed Information Retrieval of Hindi-English Tweets. Comp. y Sist. [online]. 2016, vol.20, n.3, pp.425-434. ISSN 2007-9737.  https://doi.org/10.13053/cys-20-3-2459.

Social media has become almost ubiquitous in present times. Such proliferation leads to automatic information processing need and has various challenges. The nature of social media content is mostly informal. Additionally while talking about Indian social media, users often prefer to use Roman transliterations of their native languages and English embedding. Therefore Information retrieval (IR) on such Indian social media data is a challenging and difficult task when the documents and the queries are a mixture of two or more languages written in either the native scripts and/or in the Roman transliterated form. Here in this paper we have emphasized issues related with Information Retrieval (IR) for Code-Mixed Indian social media texts, particularly texts from twitter. We describe a corpus collection process, reported limitations of available state-of-the-art IR systems on such data and formalize the problem of Code-Mixed Information Retrieval on informal texts.

Keywords : Code-mixed social media; code-mixing; code-mixed IR.

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