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        <title>CovRelex-SE: Adding Semantic Information for Relation Search via Sequence Embedding</title>
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    <abstract>In recent years, COVID-19 has impacted all aspects of human life. As a result, numerous publications relating to this disease have been issued. Due to the massive volume of publications, some retrieval systems have been developed to provide researchers with useful information. In these systems, lexical searching methods are widely used, which raises many issues related to acronyms, synonyms, and rare keywords. In this paper, we present a hybrid relation retrieval system, CovRelex-SE, based on embeddings to provide high-quality search results. Our system can be accessed through the following URL: https://www.jaist.ac.jp/is/labs/nguyen-lab/systems/covrelex-se/</abstract>
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%0 Conference Proceedings
%T CovRelex-SE: Adding Semantic Information for Relation Search via Sequence Embedding
%A Do, Truong
%A Nguyen, Chau
%A Tran, Vu
%A Satoh, Ken
%A Matsumoto, Yuji
%A Nguyen, Minh
%Y Croce, Danilo
%Y Soldaini, Luca
%S Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics: System Demonstrations
%D 2023
%8 May
%I Association for Computational Linguistics
%C Dubrovnik, Croatia
%F do-etal-2023-covrelex
%X In recent years, COVID-19 has impacted all aspects of human life. As a result, numerous publications relating to this disease have been issued. Due to the massive volume of publications, some retrieval systems have been developed to provide researchers with useful information. In these systems, lexical searching methods are widely used, which raises many issues related to acronyms, synonyms, and rare keywords. In this paper, we present a hybrid relation retrieval system, CovRelex-SE, based on embeddings to provide high-quality search results. Our system can be accessed through the following URL: https://www.jaist.ac.jp/is/labs/nguyen-lab/systems/covrelex-se/
%R 10.18653/v1/2023.eacl-demo.5
%U https://aclanthology.org/2023.eacl-demo.5
%U https://doi.org/10.18653/v1/2023.eacl-demo.5
%P 35-42

Markdown (Informal)

[CovRelex-SE: Adding Semantic Information for Relation Search via Sequence Embedding](https://aclanthology.org/2023.eacl-demo.5) (Do et al., EACL 2023)

• CovRelex-SE: Adding Semantic Information for Relation Search via Sequence Embedding (Do et al., EACL 2023)

ACL

• Truong Do, Chau Nguyen, Vu Tran, Ken Satoh, Yuji Matsumoto, and Minh Nguyen. 2023. CovRelex-SE: Adding Semantic Information for Relation Search via Sequence Embedding. In Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics: System Demonstrations, pages 35–42, Dubrovnik, Croatia. Association for Computational Linguistics.