ITM Web Conf.
Volume 54, 20232nd International Conference on Advances in Computing, Communication and Security (I3CS-2023)
|Number of page(s)||8|
|Published online||04 July 2023|
Exploring Snippets as a Dataset to Overcome Challenges in CLIR
Department of Computer Science, Babasaheb Bhimrao Ambedkar University, Lucknow, India
* Corresponding author: firstname.lastname@example.org
Cross-lingual information retrieval (CLIR) is a challenging task that requires overcoming linguistic barriers to match user queries with relevant documents in different languages. One of the major challenges in CLIR is the lack of parallel corpora, which hinders the development of effective translation models. This challenge can be addressed using snippets as a dataset to train CLIR models. Snippets can be automatically extracted from various sources, such as search engine result pages and can provide a rich and diverse set of collections for cross-lingual information retrieval. This paper initially discusses the challenges in CLIR and then explores the use of snippets as a dataset which can lead towards the development or improvements in the techniques to improve the retrieval effectiveness and further discusses the advantages and limitations of using snippets dataset in CLIR.
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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