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MSIR@FIRE: A Comprehensive Report from 2013 to 2016

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Abstract

India is a nation of geographical and cultural diversity where over 1600 dialects are spoken by the people. With the technological advancement, penetration of the internet and cheaper access to mobile data, India has recently seen a sudden growth of internet users. These Indian internet users generate contents either in English or in other vernacular Indian languages. To develop technological solutions for the contents generated by the Indian users using the Indian languages, the Forum for Information Retrieval Evaluation (FIRE) was established and held for the first time in 2008. Although Indian languages are written using indigenous scripts, often websites and user-generated content (such as tweets and blogs) in these Indian languages are written using Roman script due to various socio-cultural and technological reasons. A challenge that search engines face while processing transliterated queries and documents is that of extensive spelling variation. MSIR track was first introduced in 2013 at FIRE and the aim of MSIR was to systematically formalize several research problems that one must solve to tackle the code mixing in Web search for users of many languages around the world, develop related data sets, test benches and most importantly, build a research community focusing on this important problem that has received very little attention. This document is a comprehensive report on the 4 years of MSIR track evaluated at FIRE between 2013 and 2016.

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Notes

  1. https://bit.ly/2Hidzaq.

  2. https://bit.ly/2wkG98g.

  3. https://bit.ly/1OcHgWT.

  4. https://bit.ly/1TaOvnQ.

  5. https://bit.ly/2SW3KHf.

  6. https://bit.ly/2SW3KHf.

  7. https://bit.ly/34g3un9.

  8. https://trec.nist.gov.

  9. http://www.clef-initiative.eu/.

  10. http://ntcir.nii.ac.jp/about/.

  11. https://www.facebook.com.

  12. https://www.gutenberg.org.

  13. https://www.facebook.com.

  14. https://www.gutenberg.org.

  15. Those documents which contain duplicate content in both the scripts are ignored.

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Acknowledgements

Somnath Banerjee and Sudip Kumar Naskar are supported by Media Lab Asia, MeitY, Government of India, under the Visvesvaraya PhD Scheme for Electronics & IT. The work of Paolo Rosso was partially supported by the MISMIS research project PGC2018-096212-B-C31 funded by the Spanish MICINN.

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Authors and Affiliations

  1. Jadavpur University, Kolkata, India

    Somnath Banerjee, Sudip Kumar Naskar & Sivaji Bandyopadhyay

  2. Microsoft Research, Bangalore, India

    Monojit Choudhury

  3. NIT Agartala, Jirania, India

    Kunal Chakma

  4. IIIT Sriharikota, Sri City, India

    Amitava Das

  5. Universidad Politécnica de Valencia, Valencia, Spain

    Paolo Rosso

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  1. Somnath Banerjee
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Correspondence to Somnath Banerjee.

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This article is part of the topical collection “Forum for Information Retrieval Evaluation” guest edited by Mandar Mitra and Prasenjit Majumder.

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Banerjee, S., Choudhury, M., Chakma, K. et al. MSIR@FIRE: A Comprehensive Report from 2013 to 2016. SN COMPUT. SCI. 1, 55 (2020). https://doi.org/10.1007/s42979-019-0058-0

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