loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Robert Häusler ; Daniel Staegemann ; Matthias Volk ; Sascha Bosse ; Christian Bekel and Klaus Turowski

Affiliation: Magdeburg Research and Competence Cluster Very Large Business Applications, Faculty of Computer Science, Otto-von-Guericke University Magdeburg, Magdeburg, Germany

Keyword(s): Data Generation, Content-Compliant Data, Big Data, Education, Machine Learning.

Abstract: In order to ensure adequate education and training in a statistics-driven field, large sets of content-compliant training data (CCTD) are required. Within the context of practical orientation, such data sets should be as realistic as possible concerning the content in order to improve the learning experience. While there are different data generators for special use cases, the approaches mostly aim at evaluating the performance of database systems. Therefore, they focus on the structure but not on the content. Based on formulated requirements, this paper designs a possible approach for generating CCTD in the context of Big Data education. For this purpose, different Machine Learning algorithms could be utilized. In future work, specific models will be designed, implemented and evaluated.

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 3.15.156.140

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Häusler, R.; Staegemann, D.; Volk, M.; Bosse, S.; Bekel, C. and Turowski, K. (2020). Generating Content-Compliant Training Data in Big Data Education. In Proceedings of the 12th International Conference on Computer Supported Education - Volume 1: CSEDU; ISBN 978-989-758-417-6; ISSN 2184-5026, SciTePress, pages 104-110. DOI: 10.5220/0009513801040110

@conference{csedu20,
author={Robert Häusler. and Daniel Staegemann. and Matthias Volk. and Sascha Bosse. and Christian Bekel. and Klaus Turowski.},
title={Generating Content-Compliant Training Data in Big Data Education},
booktitle={Proceedings of the 12th International Conference on Computer Supported Education - Volume 1: CSEDU},
year={2020},
pages={104-110},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009513801040110},
isbn={978-989-758-417-6},
issn={2184-5026},
}

TY - CONF

JO - Proceedings of the 12th International Conference on Computer Supported Education - Volume 1: CSEDU
TI - Generating Content-Compliant Training Data in Big Data Education
SN - 978-989-758-417-6
IS - 2184-5026
AU - Häusler, R.
AU - Staegemann, D.
AU - Volk, M.
AU - Bosse, S.
AU - Bekel, C.
AU - Turowski, K.
PY - 2020
SP - 104
EP - 110
DO - 10.5220/0009513801040110
PB - SciTePress

- Science and Technology Publications, Lda.
RESOURCES

Proceedings

Papers

Authors

Ontology

CONTACTS

Science and Technology Publications, Lda
Avenida de S. Francisco Xavier, Lote 7 Cv. C,
2900-616 Setúbal, Portugal.

Phone: +351 265 520 185 (National fixed network call)
Fax: +351 265 520 186
Email: info@scitepress.org

EXTERNAL LINKS

PRIMORIS

INSTICC

SCITEVENTS

CROSSREF

PROCEEDINGS SUBMITTED FOR INDEXATION BY:

dblp

Ei Compendex

SCOPUS

Semantic Scholar

Google Scholar

Microsoft Academic