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Integration of Data Mining Results into Multi-dimensional Data Models

In: Information and Communication Technologies in Tourism 2015

Author

Listed:
  • Volker Meyer

    (University of Applied Sciences Ravensburg-Weingarten)

  • Wolfram Höpken

    (University of Applied Sciences Ravensburg-Weingarten)

  • Matthias Fuchs

    (Mid-Sweden University)

  • Maria Lexhagen

    (Mid-Sweden University)

Abstract

The travel and tourism domain as a global competitive service business has a special need to understand the customer and market trends. Typically, available customer-based data is stored in data warehouses and analysed by either OLAP queries or data mining techniques. However, a more powerful approach is to combine these techniques and to integrate data mining results directly into the original data warehouse structures. This comprehensive data source builds the basis for further applications of business intelligence. This paper presents a novel approach to integrate data mining results into multi-dimensional data warehouse structures and to store data mining results with the original information. A first implementation for the leading Swedish mountain destination Åre has shown the advantages of this new concept: the end-user can now easily access data mining results by simple OLAP queries and even combine them with the original information stored in the data warehouse.

Suggested Citation

  • Volker Meyer & Wolfram Höpken & Matthias Fuchs & Maria Lexhagen, 2015. "Integration of Data Mining Results into Multi-dimensional Data Models," Springer Books, in: Iis Tussyadiah & Alessandro Inversini (ed.), Information and Communication Technologies in Tourism 2015, edition 127, pages 155-168, Springer.
    • Handle: RePEc:spr:sprchp:978-3-319-14343-9_12
    DOI: 10.1007/978-3-319-14343-9_12
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    Cited by:

    1. Angeloni, Silvia, 2016. "A tourist kit ‘made in Italy’: An ‘intelligent’ system for implementing new generation destination cards," Tourism Management, Elsevier, vol. 52(C), pages 187-209.

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