MSIR@FIRE: A Comprehensive Report from 2013 to 2016

Author:

Banerjee SomnathORCID,Choudhury Monojit,Chakma Kunal,Naskar Sudip Kumar,Das Amitava,Bandyopadhyay Sivaji,Rosso Paolo

Funder

Spanish MICINN

Media Lab Asia, MeitY, Government of India

Publisher

Springer Science and Business Media LLC

Reference41 articles.

1. Ahmed UZ, Bali K, Choudhury M, Sowmya VB. Challenges in designing input method editors for Indian languages: the role of word-origin and context. In: Advances in text input methods (WTIM 2011). 2011. pp. 1–9

2. Banerjee S, Chakma K, Naskar SK, Das A, Rosso P, Bandyopadhyay S, Choudhury M. Overview of the mixed script information retrieval (MSIR) at fire-2016. In: Forum for information retrieval evaluation. Springer; 2016. pp. 39–49.

3. Banerjee S, Kuila A, Roy A, Naskar SK, Rosso P, Bandyopadhyay S. A hybrid approach for transliterated word-level language identification: CRF with post-processing heuristics. In: Proceedings of the forum for information retrieval evaluation, ACM, 2014. pp. 54–59.

4. Banerjee S, Naskar S, Rosso P, Bandyopadhyay S. Code mixed cross script factoid question classification—a deep learning approach. J Intell Fuzzy Syst. 2018;34(5):2959–69.

5. Banerjee S, Naskar SK, Rosso P, Bandyopadhyay S. The first cross-script code-mixed question answering corpus. In: Proceedings of the workshop on modeling, learning and mining for cross/multilinguality (MultiLingMine 2016), co-located with the 38th European Conference on Information Retrieval (ECIR). 2016.

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1. Language Resource Acquisition for Low-Resource Languages in Digital Discourses;Advances in Computational Intelligence and Robotics;2024-02-27

2. Usefulness of Graphemes in Word-Level Language Identification in Code-Mixed Text;Lecture Notes in Networks and Systems;2022

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