NCC: Neural concept compression for multilingual document recommendation

Tashu, Tsegaye Misikir; Lenz, Marc; Horváth, Tomáš

Abstract

In this work, we propose a novel method for generating inter-lingual document representations using neural network concept compression. The presented approach is intended to improve the quality of content-based multilingual document recommendation and information retrieval systems by creating a language-independent representation. The main idea is to use mappings to align monolingual representation spaces, using concept compression, to create inter-lingual representations. The proposed approach outperforms traditional cross-lingual retrieval and recommendations methods in experiments conducted on JRC-Acquis and EU bookshop multilingual corpora. Our dataset and code are publicly available at https://github.com/Tsegaye-misikir/NCC.

Citation

Tashu, T. M., Lenz, M., & Horváth, T. NCC: Neural concept compression for multilingual document recommendation

• Presentation Conference Type: Conference Paper (published)
• Acceptance Date: Apr 21, 2023
• Online Publication Date: Apr 27, 2023
• Publication Date: 2023-07
• Deposit Date: Mar 27, 2024
• Journal: Applied Soft Computing
• Print ISSN: 1568-4946
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 142
• Article Number: 110348
• DOI: https://doi.org/10.1016/j.asoc.2023.110348
• Keywords: Information retrieval, Document representation, Natural language processing, Cross-lingual representation, Multi-lingual recommendation
• Public URL: http://researchrepository.napier.ac.uk/Output/3577408