Formal Concept Analysis for Qualitative Data Analysis over Triple Stores

  • Frithjof Dau
  • Bariş Sertkaya
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6999)

Abstract

Business Intelligence solutions provide different means like OLAP, data mining or case based reasoning to explore data. Standard BI means are usually based on mathematical statistics and provide a quantitative analysis of the data. In this paper, a qualitative approach based on a mathematical theory called ”Formal Concept Analysis” (FCA) is used instead. FCA allows clustering a given set of objects along attributes acting on the objects, hierarchically ordering those clusters, and finally visualizing the cluster hierarchy in so-called Hasse-diagrams. The approach in this paper is exemplified on a dataset of documents crawled from the SAP community network, which are persisted in a semantic triple store and evaluated with an existing FCA tool called ”ToscanaJ” which has been modified in order to retrieve its data from a triple store.

Keywords

Association Rule Formal Concept Case Base Reasoning Concept Lattice Qualitative Data Analysis 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Frithjof Dau
    • 1
  • Bariş Sertkaya
    • 1
  1. 1.SAP Research CenterDresdenGermany

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