Abstract
Data mining is a recent development in the field of database exploration. A powerful and well investigated topic is the discovery of association rules. This paper examines the use of association rules within the domain of facilities management. Within such a domain the application of association rules offers a way of identifying relationships between sets of data which may previously have been thought to be completely unrelated. We describe algorithms for the development of association graphs and expansion trees to.identify such relationships in response to loosely defined user queries. This provides a means to examine many possible relationships prior to exposing an interesting one.
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References
Agrawal, R. Imielinski, T. Swami, A. Mining Association Rules Between Sets of Items in Large Databases. SIGMOD-93, 207–216. May 1993.
Frost, R.A. Introduction to Knowledge Based Systems. Collins. 1986.
Further Education Funding Council Effective Facilities Management: A Good Practice Guide. Her Majesty’s Stationery Office. 1997
Manilla, H. Toivonen, H. Verkamo, A.I. Improved Methods for Finding Association Rules. University of Helsinki, Department of Computer Science. Publication C, No. C-1993–65. 1994.
Toivonen, H. Sampling Large Databases for Association Rules. Proceedings of 22nd VLDB Conference pp 134–145. 1996.
Yen, S.J. Chen,A.L.P. An Efficient Data Mining Technique for Discovering Association Rules. DEXA. IEEE Computer Society Press. 1997.
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© 1999 Springer-Verlag London
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Goulbourne, G., Coenen, F., Leng, P., Murphy, D. (1999). Developing Association Rules in Facilities Management Databases. In: Milne, R.W., Macintosh, A.L., Bramer, M. (eds) Applications and Innovations in Expert Systems VI. Springer, London. https://doi.org/10.1007/978-1-4471-0575-6_17
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DOI: https://doi.org/10.1007/978-1-4471-0575-6_17
Publisher Name: Springer, London
Print ISBN: 978-1-85233-087-3
Online ISBN: 978-1-4471-0575-6
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