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2015 | OriginalPaper | Chapter

9. Clustering Items in Time-Stamped Databases

Authors : Animesh Adhikari, Jhimli Adhikari

Published in: Advances in Knowledge Discovery in Databases

Publisher: Springer International Publishing

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Abstract

Many multi-branch companies transact from different branches. Each branch of the company maintains a separate database over time. The variation of sales of an item over time is an important issue, and therefore, we present the notion of stability of an item. Stable items are useful in making numerous strategic decisions of the company. We have discussed two measures of stability of an item. Based on the degree of stability of an item, an algorithm is designed for finding partition among items in different data sources. Then the notion of the best cluster is introduced by considering average degree of variation of a class, and designed an algorithm to find clusters among items in different data sources. The best cluster is determined by average degree of variation in a cluster. Experimental results are provided for three transactional databases.

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previous chapter Synthesizing Exceptional Patterns in Different Data Sources
next chapter Synthesizing Some Extreme Association Rules from Multiple Databases
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Metadata
Title
Clustering Items in Time-Stamped Databases
Authors
Animesh Adhikari
Jhimli Adhikari
Copyright Year
2015
Book
Advances in Knowledge Discovery in Databases

Print ISBN: 978-3-319-13211-2

Electronic ISBN: 978-3-319-13212-9

Copyright Year: 2015

DOI
https://doi.org/10.1007/978-3-319-13212-9_9

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