ExpEngine: A Tool for Data Analytics Workflow Optimization Through User-Driven Experimentation
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F24%3A10490957" target="_blank" >RIV/00216208:11320/24:10490957 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1109/ACSOS-C63493.2024.00058" target="_blank" >https://doi.org/10.1109/ACSOS-C63493.2024.00058</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ACSOS-C63493.2024.00058" target="_blank" >10.1109/ACSOS-C63493.2024.00058</a>
Alternative languages
Result language
angličtina
Original language name
ExpEngine: A Tool for Data Analytics Workflow Optimization Through User-Driven Experimentation
Original language description
With the exponential growth of data analytics workflows, optimizing them has become crucial. In particular, there is a need to go beyond what the AutoML tools currently offer by considering different aspects of users (domain experts and data scientists) in the optimization process. Responding to this need, we propose a tool framework comprising an Experimentation Engine and a Domain-Specific Language. Together, they allow users to specify not only what needs to be optimized, but also how: in which steps, and with the desired degree of user involvement. The sources and demo video of our tool framework are available at https://github.com/ExtremeXP-VU/ExpEngine-ACSOS2024.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Companion Proceedings of 2024 IEEE International Conference on Autonomic Computing and Self-Organizing Systems, ACSOS-C 2024
ISBN
979-8-3503-8976-0
ISSN
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e-ISSN
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Number of pages
2
Pages from-to
182-183
Publisher name
IEEE
Place of publication
USA
Event location
Aarhus, Denmark
Event date
Sep 16, 2024
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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