TY - JOUR
T1 - NCC
T2 - Neural concept compression for multilingual document recommendation[Formula presented]
AU - Tashu, Tsegaye Misikir
AU - Lenz, Marc
AU - Horváth, Tomáš
N1 - Funding Information:
This research is supported by the ÚNKP-22-4 New National Excellence Program of the Ministry for Innovation and Technology from the source of the National Research, Development and Innovation Fund . “Application Domain Specific Highly Reliable IT Solutions” project has been implemented with the support provided from the National Research, Development and Innovation Fund of Hungary , financed under the Thematic Excellence Programme TKP2020-NKA-06 (National Challenges Subprogramme) funding scheme.
Publisher Copyright:
© 2023
PY - 2023/7
Y1 - 2023/7
N2 - 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.
AB - 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.
KW - Cross-lingual representation
KW - Document representation
KW - Information retrieval
KW - Multi-lingual recommendation
KW - Natural language processing
UR - http://www.scopus.com/inward/record.url?scp=85156200092&partnerID=8YFLogxK
U2 - 10.1016/j.asoc.2023.110348
DO - 10.1016/j.asoc.2023.110348
M3 - Article
AN - SCOPUS:85156200092
SN - 1568-4946
VL - 142
JO - Applied Soft Computing
JF - Applied Soft Computing
M1 - 110348
ER -