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DC Field | Value | Language |
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dc.contributor.author | Vázquez-Ingelmo, A. | - |
dc.contributor.author | García-Peñalvo, F. J. | - |
dc.contributor.author | Therón, R. | - |
dc.date.accessioned | 2021-09-20T17:24:29Z | - |
dc.date.available | 2021-09-20T17:24:29Z | - |
dc.date.issued | 2020-10-21 | - |
dc.identifier.citation | Vázquez-Ingelmo, A., García-Peñalvo, F. J., & Therón, R. (2020). Advances in the use of domain engineering to support feature identification and generation of information visualizations. In F. J. García-Peñalvo (Ed.), Proceedings TEEM’20. Eighth International Conference on Technological Ecosystems for Enhancing Multiculturality (Salamanca, Spain, October 21st - 23rd, 2020). ACM. https://doi.org/10.1145/3434780.3436640 | en |
dc.identifier.isbn | 978-1-4503-8850-4 | - |
dc.identifier.uri | http://repositorio.grial.eu/handle/grial/2375 | - |
dc.description.abstract | Information visualization tools are widely used to better understand large and complex datasets. However, to make the most out of them, it is necessary to rely on proper designs that consider not only the data to be displayed, but also the audience and the context. There are tools that already allow users to configure their displays without requiring programming skills, but this research project aims at exploring the automatic generation of information visualizations and dashboards in order to avoid the configuration process, and select the most suitable features of these tools taking into account their contexts. To address this problem, a domain engineering, and machine learning approach is proposed. | en |
dc.language.iso | en | en |
dc.publisher | ACM | en |
dc.subject | Automatic generation | en |
dc.subject | Machine Learning | en |
dc.subject | Domain engineering | en |
dc.subject | Meta-modeling | en |
dc.subject | Information Dashboards | en |
dc.subject | High-level requirements | en |
dc.title | Advances in the use of domain engineering to support feature identification and generation of information visualizations | en |
dc.type | Article | en |
Appears in Collections: | Publications |
Files in This Item:
File | Description | Size | Format | |
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Andrea-post.pdf | Article | 547,3 kB | Adobe PDF | View/Open |
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