Author ORCID Identifier
0000000344134476
Document Type
Conference Paper
Rights
Available under a Creative Commons Attribution Non-Commercial Share Alike 4.0 International Licence
Disciplines
1.2 COMPUTER AND INFORMATION SCIENCE, Information Science
Abstract
To assist the COVID-19 focused researchers in life science and healthcare in understanding the pandemic, we present an exploratory information retrieval system called RCES. The system employs a previously developed EVE (Explainable Vector-based Embedding) model using DBpedia and an adopted model using MeSH taxonomies to exploit concept relations related to COVID-19. Various expansion methods are also developed, along with explanations and facets that collectively form rapid cues for a valuable navigational and informed user experience.
DOI
https://doi.org/10.1145/3459637.3481990
Recommended Citation
Wei Li, Rishi Choudhary, Arjumand Younus, Bruno Ohana, Nicole Baker, Brendan Leen, and M. Atif Qureshi. 2021. RCES: Rapid Cues Exploratory Search Using Taxonomies For COVID-19. In Proceedings of the 30th ACM International Conference on Information and Knowledge Management (CIKM ’21), November 1–5, 2021, Virtual Event, QLD, Australia. ACM, New York, NY, USA, 5 pages. https://doi.org/10.1145/3459637.3481990
Funder
Science Foundation Ireland
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 4.0 International License.
Publication Details
In Proceedings of the 30th ACM International Conference on Information and Knowledge Management (CIKM ’21), November 1–5, 2021