Abstract
Knowledge discovery is the effort to find information from data. In contemporary terms, it is the application of tools (from statistics and from artificial intelligence) to extract interesting patterns from data stored in large databases. Here interesting means non-trivial, implicit, previously unknown, and easily understood and described knowledge that can be used ( actionable ).
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Agrawal R, Imielinski T, Swami A (1993) Database mining: a performance perspective. IEEE Trans Knowl Data Eng 5(6):914–925
Aguinis H, Forcum LE, Joo H (2013) Using market basket analysis in management research. J Manag 39(7):1799–1824
Berry MJA, Linoff G (1997) Data mining techniques. John Wiley & Sons, New York
Vindevogel B, Van den Poel D, Wets G (2005) Why promotion strategies based on market basket analysis do not work. Expert Syst Appl 28:583–590
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2017 Springer Nature Singapore Pte Ltd.
About this chapter
Cite this chapter
Olson, D.L. (2017). Market Basket Analysis. In: Descriptive Data Mining. Computational Risk Management. Springer, Singapore. https://doi.org/10.1007/978-981-10-3340-7_3
Download citation
DOI: https://doi.org/10.1007/978-981-10-3340-7_3
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-3339-1
Online ISBN: 978-981-10-3340-7
eBook Packages: Business and ManagementBusiness and Management (R0)