A Comparison of Two Database Partitioning Approaches that Support Taxonomy-Based Query Answering
Authors: 
Jero Mario Schäfer and Lena WieseAuthors Info & Claims
Jero Mario Schäfer and Lena WieseAuthors Info & ClaimsNovember 2020
Pages 426 - 435
Abstract
In this paper we address the topic of identification of cohorts of similar patients in a database of electronic health records. We follow the conjecture that retrieval of similar patients can be supported by an underlying distributed database design. Hence we propose a fragmentation based on partitioning the health records and present a benchmark of two implementation variants in comparison to an off-the-shelf data distribution approach provided by Apache Ignite. While our main use case in this paper is cohort identification, our approach has advantages for taxonomy-based query answering in other (non-medical) domains.
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- A Comparison of Two Database Partitioning Approaches that Support Taxonomy-Based Query Answering
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November 2020
492 pages
ISBN:9781450389228
DOI:10.1145/3428757
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Published: 27 January 2021
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iiWAS '20
iiWAS '20: The 22nd International Conference on Information Integration and Web-based Applications & Services
November 30 - December 2, 2020
Chiang Mai, Thailand
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