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Title:
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LINGUISTIC SUMMARIZATION FOR BUSINESS INTELLIGENCE USING THE TIME DIMENSION IN DATA WAREHOUSES |
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Author(s):
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Rita Castillo-ortega , Nicolás Marín , Daniel Sánchez |
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ISBN:
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978-972-8924-97-3 |
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Editors:
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Hans Weghorn and Pedro Isaías |
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Year:
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2009 |
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Edition:
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V I, 2 |
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Keywords:
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Linguistic summarization, Time series, Dimensional data model, OLAP, Business Intelligence, Fuzzy Logic. |
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Type:
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Full Paper |
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First Page:
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19 |
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Last Page:
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26 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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The Data Warehouse model is based on the use of the Multi-dimensional Data Model. Its basic structures are Data Cubes.
The main purpose of this model is to store data but it also includes the means to retrieve, analize, extract, transform and
load data. Conventional database models are not appropriated for friendly ad-hoc analysis and display of large amounts
of data, both of them needed by decision support systems. Data Warehouse allows us to deal with these limitations.
Among the different dimensions that are usually included in data cubes we could find the temporal dimension as one of
the most important. Time series data representing user necessities of information, can be extracted from data cubes by
means of OnLine Analytical Processing operations over the previously mentioned temporal dimension. In this paper, we
present a new approach to accomplish linguistic summarization of data in data cubes containing historical information
using fuzzy quantified statements. The basis of our approach is a time dimension defined by the user as a hierarchical
collection of fuzzy time periods. |
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