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Issue:Temporality and intuitionistic fuzzy data warehouses: Difference between revisions
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| title = Temporality and intuitionistic fuzzy data warehouses | | title = Temporality and intuitionistic fuzzy data warehouses | ||
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| conference = Eighth [[International Conference on Intuitionistic Fuzzy Sets]], Varna, 20-21 June 2004 | | conference = Eighth [[International Conference on Intuitionistic Fuzzy Sets]], Varna, 20-21 June 2004 | ||
| issue = [[Notes on Intuitionistic Fuzzy Sets/10/4|"Notes on Intuitionistic Fuzzy Sets", Volume 10 (2004) Number 4]], pages | | issue = [[Notes on Intuitionistic Fuzzy Sets/10/4|"Notes on Intuitionistic Fuzzy Sets", Volume 10 (2004) Number 4]], pages 47-55 | ||
| file = NIFS-10-4- | | file = NIFS-10-4-47-55.pdf | ||
| format = PDF | | format = PDF | ||
| size = | | size = 9935 | ||
| abstract = Data warehouse is an amalgamated view on the data within an enterprise and a first step in integrating enterprise systems. Data warehouses are used for analysing enterprise data online, offering the possibility to aggregate and compare data along dimensions relevant in the application domain. In intuitionistic fuzzy data warehouses each object has its degree of compliance and non-compliance. Typically time is one of the dimensions we find in data warehouses allowing comparisons of different periods. The instances of dimensions, however, change over time, organisations unite and separate, organisational structures emerge and vanish, or evolve. In current data warehouse architectures these changes cannot be represented adequately since all dimensions are considered as orthogonal, putting restrictions on the validity of queries defined over several eras. In this paper we propose an architecture for temporal data warehouse systems, which allows the accommodation of the temporal dimension of data belonged to evolving hierarchical structures. We present how uncertainty in the time component influences the degrees of compliance of the information. | | abstract = Data warehouse is an amalgamated view on the data within an enterprise and a first step in integrating enterprise systems. Data warehouses are used for analysing enterprise data online, offering the possibility to aggregate and compare data along dimensions relevant in the application domain. In intuitionistic fuzzy data warehouses each object has its degree of compliance and non-compliance. Typically time is one of the dimensions we find in data warehouses allowing comparisons of different periods. The instances of dimensions, however, change over time, organisations unite and separate, organisational structures emerge and vanish, or evolve. In current data warehouse architectures these changes cannot be represented adequately since all dimensions are considered as orthogonal, putting restrictions on the validity of queries defined over several eras. In this paper we propose an architecture for temporal data warehouse systems, which allows the accommodation of the temporal dimension of data belonged to evolving hierarchical structures. We present how uncertainty in the time component influences the degrees of compliance of the information. | ||
| keywords = data warehouse, intuitionistic fuzzy sets, OLAP, temporality | | keywords = data warehouse, intuitionistic fuzzy sets, OLAP, temporality |
Latest revision as of 18:48, 28 August 2024
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Categories:
- Publications on intuitionistic fuzzy sets
- Publications in Notes on IFS
- Publications in 2004 year
- ICIFS conference publications
- Publications of Panagiotis Chountas
- Publications of Ilias Petrounias
- Publications of Chris Vasilakis
- Publications of Elia El-Darzi
- Publications of Andy Tseng
- Publications of Boyan Kolev
- Publications of Vassilis Kodogiannis
- Publications of Peter Georgiev