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Innovative Approaches for Efficiently Warehousing Complex Data from the Web
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Author(s): Fadila Bentayeb (University of Lyon, France), Nora Maïz (University of Lyon, France), Hadj Mahboubi (CEMAGREF Centre Clermont-Ferrand, France), Cécile Favre (University of Lyon, France), Sabine Loudcher (University of Lyon, France), Nouria Harbi (University of Lyon, France), Omar Boussaïd (University of Lyon, France)and Jérôme Darmont (University of Lyon, France)
Copyright: 2012
Pages: 27
Source title:
Business Intelligence Applications and the Web: Models, Systems and Technologies
Source Author(s)/Editor(s): Marta E. Zorrilla (University of Cantabria, Spain), Jose-Norberto Mazón (University of Alicante, Spain), Óscar Ferrández (University of Alicante, Spain), Irene Garrigós (University of Alicante, Spain), Florian Daniel (University of Trento, Italy)and Juan Trujillo (University of Alicante, Spain)
DOI: 10.4018/978-1-61350-038-5.ch002
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Abstract
Research in data warehousing and OLAP has produced important technologies for the design, management, and use of Information Systems for decision support. With the development of Internet, the availability of various types of data has increased. Thus, users require applications to help them obtaining knowledge from the Web. One possible solution to facilitate this task is to extract information from the Web, transform and load it to a Web Warehouse, which provides uniform access methods for automatic processing of the data. In this chapter, we present three innovative researches recently introduced to extend the capabilities of decision support systems, namely (1) the use of XML as a logical and physical model for complex data warehouses, (2) associating data mining to OLAP to allow elaborated analysis tasks for complex data and (3) schema evolution in complex data warehouses for personalized analyses. Our contributions cover the main phases of the data warehouse design process: data integration and modeling, and user driven-OLAP analysis.
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