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OLAP on Information Networks: A New Framework for Dealing with Bibliographic Data

  • Wararat Jakawat
  • Cécile Favre
  • Sabine Loudcher
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 241)

Abstract

In the context of decision making, data warehouses support OLAP technology and they have been very useful for efficient analysis onto structured data. For several years, OLAP is also used to analyze and visualize more complex data. Now, many data sets of interest can be described as a linked collection of interrelated objects. They could be represented as heterogeneous information networks, in which there are multiple object and link types. In this paper, we are focusing on bibliographic data. This type of data constitutes a rich source that is the starting point of research on bibliometrics, scientometrics domains. In this context, we discuss the interest of combining information networks, OLAP and data mining technologies. We propose a framework to materialize this combination and discuss the main challenges to build this framework. The basic idea is to be able to analyze various networks built from the bibliographic data representing different points of view (authors networks, citations networks...) and their dynamic.

Keywords

OLAP Data Warehouse Information Networks Bibliographic Data Data Mining 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Wararat Jakawat
    • 1
  • Cécile Favre
    • 1
  • Sabine Loudcher
    • 1
  1. 1.Université de Lyon (ERIC LYON 2)LyonFrance

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