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2015 | OriginalPaper | Buchkapitel

Integration of Data Mining Results into Multi-dimensional Data Models

verfasst von : Volker Meyer, Wolfram Höpken, Matthias Fuchs, Maria Lexhagen

Erschienen in: Information and Communication Technologies in Tourism 2015

Verlag: Springer International Publishing

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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.

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Vorheriges Kapitel An Application of Apriori Algorithm Association Rules Mining to Profiling the Heritage Visitors of Macau

Nächstes Kapitel A Practical Approach to Big Data in Tourism: A Low Cost Raspberry Pi Cluster

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Titel: Integration of Data Mining Results into Multi-dimensional Data Models
verfasst von: Volker Meyer
Wolfram Höpken
Matthias Fuchs
Maria Lexhagen
Verlag: Springer International Publishing
Buch: Information and Communication Technologies in Tourism 2015
Print ISBN: 978-3-319-14342-2

Electronic ISBN: 978-3-319-14343-9

Copyright-Jahr: 2015
DOI: https://doi.org/10.1007/978-3-319-14343-9_12

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