| Title of paper:
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Temporality and intuitionistic fuzzy data warehouses
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| Author(s):
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| Panagiotis Chountas
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| Health Care Computing Group, School of Computer Science, University of Westminster, Watford Road, Northwick Park, London, HA1l 3TP, UK
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| chountp@wmin.ac.uk
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| Ilias Petrounias
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| Department of Computation, UMIST, PO Box 88, Manchester M60 1QD, UK
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| Chris Vasilakis
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| Health Care Computing Group, School of Computer Science, University of Westminster, Watford Road, Northwick Park, London, HA1l 3TP, UK
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| Elia El-Darzi
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| Health Care Computing Group, School of Computer Science, University of Westminster, Watford Road, Northwick Park, London, HA1l 3TP, UK
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| Andy Tseng
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| Department of Computation, UMIST, PO Box 88, Manchester M60 1QD, UK
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| Boyan Kolev
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| CLBME — Bulgarian Academy of Sciences, Bl. 105, Sofia-1113, BULGARIA
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| Vassilis Kodogiannis
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| Health Care Computing Group, School of Computer Science, University of Westminster, Watford Road, Northwick Park, London, HA1l 3TP, UK
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| Peter Georgiev
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| CLBME — Bulgarian Academy of Sciences, Bl. 105, Sofia-1113, BULGARIA
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| Presented at:
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Eighth International Conference on Intuitionistic Fuzzy Sets, Varna, 20-21 June 2004
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| Published in:
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"Notes on Intuitionistic Fuzzy Sets", Volume 10 (2004) Number 4, pages 70-74
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| Download:
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 PDF (4784 Kb, File info)
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| Abstract:
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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.
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| Keywords:
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data warehouse, intuitionistic fuzzy sets, OLAP, temporality
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| References:
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