Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/71910
Título: | Discovering analytical preferences for personalizing what-if scenarios |
Autor(es): | Carvalho, Mariana Belo, Orlando |
Palavras-chave: | Alloy formal specification Business intelligence OLAP personalization On-Line Analytical Processing Usage preferences What-If analysis |
Data: | 2019 |
Editora: | Springer, Cham |
Revista: | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
Citação: | Carvalho M., Belo O. (2019) Discovering Analytical Preferences for Personalizing What-If Scenarios. In: Moura Oliveira P., Novais P., Reis L. (eds) Progress in Artificial Intelligence. EPIA 2019. Lecture Notes in Computer Science, vol 11805. Springer, Cham. https://doi.org/10.1007/978-3-030-30244-3_35 |
Resumo(s): | In this paper, we expose a hybridization methodology for helping to overcome the pitfalls of conventional What-If analysis process design and development by discovering the best recommendations for What-If analysis scenarios’ parameters using OLAP preferences. The hybridization process aims at assisting users during the decision-making processes by suggesting the most adequate scenario parameters according to their needs, making What-If scenarios more valuable, helping them during decision-making processes. The hybridization process provides several advantages to companies by making possible to study the behavior of a system without building it or creating the circumstances to make it happen in a business real-world system. Thus, knowing existing approaches for extracting preferences when dealing with OLAP application environments has clear business advantages. This work is about this, with a particular focus on discovering analytical preferences for personalizing What-If application scenarios. |
Tipo: | Artigo em ata de conferência |
URI: | https://hdl.handle.net/1822/71910 |
ISBN: | 978-3-030-30243-6 |
e-ISBN: | 978-3-030-30244-3 |
DOI: | 10.1007/978-3-030-30244-3_35 |
ISSN: | 0302-9743 |
Versão da editora: | https://link.springer.com/chapter/10.1007%2F978-3-030-30244-3_35 |
Arbitragem científica: | yes |
Acesso: | Acesso restrito UMinho |
Aparece nas coleções: |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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2019-CI-Epia-KBDI-Carvalho&Belo-CRP.pdf Acesso restrito! | 593,9 kB | Adobe PDF | Ver/Abrir |