Linear Concept Approximation for Multilingual Document Recommendation

Salamon, Vilmos Tibor; Tashu, Tsegaye Misikir; Horváth, Tomáš

Abstract

In this paper, we proposed Linear Concept Approximation, a novel multilingual document representation approach for the task of multilingual document representation and recommendation. The main idea is in creating representations by using mappings to align monolingual representation spaces using linear concept approximation, that in turn will enhance the quality of content-based Multilingual Document Recommendation Systems. The experimental results on JRC-Acquis have shown that our proposed approach outperformed traditional methods on the task of multilingual document recommendation.

Citation

Salamon, V. T., Tashu, T. M., & Horváth, T. (2021). Linear Concept Approximation for Multilingual Document Recommendation. . Springer. https://doi.org/10.1007/978-3-030-91608-4_15

• Online Publication Date: Nov 23, 2021
• Publication Date: 2021
• Deposit Date: Apr 8, 2024
• Publisher: Springer
• Pages: 147-156
• Series Title: Lecture Notes in Computer Science
• Series Number: 13113
• Series ISSN: 0302-9743
• ISBN: 9783030916077
• DOI: https://doi.org/10.1007/978-3-030-91608-4_15
• Keywords: Multilingual representation learning, Latent semantic indexing, Document recommendation, Multilingual NLP
• Public URL: http://researchrepository.napier.ac.uk/Output/3587404