Multidimensional ontology-based visual ranking
| Autor: | Evangelia Triperina |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Structure (mathematical logic)
Visual analytics Decision support system Information retrieval Visual perception Exploit Computer science 05 social sciences General Engineering 02 engineering and technology Ontology (information science) 050905 science studies Ranking (information retrieval) 020204 information systems 0202 electrical engineering electronic engineering information engineering General Earth and Planetary Sciences 0509 other social sciences Semantic Web General Environmental Science |
| Zdroj: | ACM SIGWEB Newsletter. 2020:1-4 |
| ISSN: | 1931-1435 1931-1745 |
| DOI: | 10.1145/3409481.3409483 |
| Popis: | Evangelia Triperina obtained her PhD in Computer Sciences from the University of Limoges, France in 2020. Her thesis focuses on the interdisciplinary research in multidimensional decisions support in the ranking problematic aided by visual analytics and semantic web technologies. Interactive visual analytics exploit the increased visual perceptual abilities of the decision makers creating a more efficient decision support procedure, while semantic web technologies, and more specifically ontologies, structure data, make the system dynamic and add several needed capabilities to the decision support system. Furthermore, the multidimensional decision support method relies not only on evaluating an alternative based on multiple criteria, but also on important dimensions of the domain 1 . |
| Databáze: | OpenAIRE |
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