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European Big Data Management and Analytics Summer School

eBISS 2011: Business Intelligence pp 84–97Cite as

The GoOLAP Fact Retrieval Framework

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Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 96))

Summary

We discuss the novel problem of supporting analytical business intelligence queries over web-based textual content, e.g., BI-style reports based on 100.000’s of documents from an ad-hoc web search result. Neither conventional search engines nor conventional Business Intelligence and ETL tools address this problem, which lies at the intersection of their capabilities. Three recent developments have the potential to become key components of such an ad-hoc analysis platform: significant improvements in cloud computing query languages, advances in self-supervised keyword generation techniques and powerful fact extraction frameworks. We will give an informative and practical look at the underlying research challenges in supporting ”Web-Scale Business Analytics” applications that we met when building GoOLAP, a system that already enjoys a broad user base and over 6 million objects and facts.

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Author information

Authors and Affiliations

  1. FG DIMA, Technische Universität Berlin, Berlin, Germany

    Alexander Löser, Sebastian Arnold & Tillmann Fiehn

Authors
  1. Alexander Löser
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  2. Sebastian Arnold
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  3. Tillmann Fiehn
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Editor information

Editors and Affiliations

  1. MAS Laboratory, Ecole Centrale Paris, 92 295, Châtenay-Malabry Cedex, France

    Marie-Aude Aufaure

  2. Department of Computer & Decision Engineering (CoDE) CP 165/15, Universite Libre de Bruxelles, 1050, Brussels, Belgium

    Esteban Zimányi

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Löser, A., Arnold, S., Fiehn, T. (2012). The GoOLAP Fact Retrieval Framework. In: Aufaure, MA., Zimányi, E. (eds) Business Intelligence. eBISS 2011. Lecture Notes in Business Information Processing, vol 96. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27358-2_4

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  • DOI: https://doi.org/10.1007/978-3-642-27358-2_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-27357-5

  • Online ISBN: 978-3-642-27358-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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