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Preserving Contextual Information in Relational Matrix Operations

Dolmatova, Oksana; Augsten, Nikolaus; Böhlen, Michael Hanspeter (2020). Preserving Contextual Information in Relational Matrix Operations. In: 36th IEEE International Conference on Data Engineering, ICDE 2020, Dallas, TX, USA, 20 April 2020 - 24 April 2020. IEEE, 1894-1897.

Abstract

There exist large amounts of numerical data that are stored in databases and must be analyzed. Database tables come with a schema and include non-numerical attributes; this is crucial contextual information that is needed for interpreting the numerical values. We propose relational matrix operations that support the analysis of data stored in tables and that preserve contextual information. The result of our approach are precisely defined relational matrix operations and a system implementation in MonetDB that illustrates the seamless integration of relational matrix operations into a relational DBMS.

Additional indexing

Item Type:Conference or Workshop Item (Paper), refereed, original work
Communities & Collections:03 Faculty of Economics > Department of Informatics
Dewey Decimal Classification:000 Computer science, knowledge & systems
Scopus Subject Areas:Physical Sciences > Software
Physical Sciences > Signal Processing
Physical Sciences > Information Systems
Scope:Discipline-based scholarship (basic research)
Language:English
Event End Date:24 April 2020
Deposited On:01 Mar 2021 08:48
Last Modified:06 Mar 2024 14:34
Publisher:IEEE
OA Status:Green
Publisher DOI:https://doi.org/10.1109/ICDE48307.2020.00197
Other Identification Number:merlin-id:20728
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