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Neural Methods for Cross-Language Information Retrieval

Published: 18 July 2023 Publication History

Abstract

This half day tutorial introduces the participant to the basic concepts underlying neural Cross-Language Information Retrieval (CLIR). It discusses the most common algorithmic approaches to CLIR, focusing on modern neural methods; the history of CLIR; where to find and how to use CLIR training collections, test collections and baseline systems; how CLIR training and test collections are constructed; and open research questions in CLIR.

References

[1]
Payal Bajaj, Daniel Campos, Nick Craswell, Li Deng, Jianfeng Gao, Xiaodong Liu, Rangan Majumder, Andrew McNamara, Bhaskar Mitra, Tri Nguyen, et al. 2016. MS MARCO: A human generated machine reading comprehension dataset. arXiv preprint arXiv:1611.09268 (2016).
[2]
Petra Galuscáková, Douglas W Oard, and Suraj Nair. 2021. Cross-language information retrieval. arXiv preprint arXiv:2111.05988 (2021).
[3]
Sean MacAvaney, Andrew Yates, Sergey Feldman, Doug Downey, Arman Cohan, and Nazli Goharian. 2021. Simplified Data Wrangling with ir_datasets. In Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR).
[4]
Jian-Yun Nie. 2010. Cross-Language Information Retrieval. Morgan & Claypool Publishers. https://doi.org/10.2200/S00266ED1V01Y201005HLT008

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Published In

cover image ACM Conferences
SIGIR '23: Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval
July 2023
3567 pages
ISBN:9781450394086
DOI:10.1145/3539618
This work is licensed under a Creative Commons Attribution-ShareAlike International 4.0 License.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 18 July 2023

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Author Tags

  1. CLIR
  2. cross-language information retrieval
  3. tutorial

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  • Tutorial

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SIGIR '23
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