Fuzzy quantification-based linguistic summaries in data cubes with hierarchical fuzzy partition of time dimension

Authors:
Rita Castillo-Ortega;Nicolás Marín;Daniel Sánchez
Affiliations:
Intelligent Databases and Information Systems Research Group, Deparment of Computer Science and A.I., University of Granada, Granada, Spain;Intelligent Databases and Information Systems Research Group, Deparment of Computer Science and A.I., University of Granada, Granada, Spain;Intelligent Databases and Information Systems Research Group, Deparment of Computer Science and A.I., University of Granada, Granada, Spain
Venue:
IDEAL'09 Proceedings of the 10th international conference on Intelligent data engineering and automated learning
Year:
2009

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Abstract

Data Cubes are the basic structure of the Multi-dimensional DataModel. OnLine Analytical Processing techniques together with data cubes come to overcome the limitation of conventional database models whose structures are not well suited for the friendly ad-hoc analysis and display of large amounts of data decision support systems need. One of the dimensions that usually appears in data cubes is the time dimension. The use of OnLine Analytical Processing operations through this dimension produces as result time series data that ask for suitable summarization techniques in order to effectively present the information to the interested user. Soft Computing approaches to data summarization are widely used to carry out this task. In this paper, we introduce an approach to linguistic summarization of data in data cubes with time dimension using fuzzy quantified statements. Our approach uses as basis a time dimension defined by the user as a hierarchical collection of fuzzy time periods.