Abstract
As e-business software prevails worldwide, large amount of data are accumulated automatically in databases of most sizable companies. Managers in organizations now face the problems of making sense out of the data. In this paper, an algorithm to automatically produce characteristic rules to describe the major characteristics of data in a table is proposed. In contrast to traditional Attribute Oriented Induction methods, the algorithm, named as Char Algorithm, does not need a concept tree and only requires setting a desired coverage threshold to generate a minimal set of characteristic rules to describe the given dataset. Our simulation results show that the characteristic rules found by Char are fairly consistent even when the number of records and attributes increase.
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Liu, YC., Hsu, PY. (2004). Char: An Automatic Way to Describe Characteristics of Data. In: Yang, Z.R., Yin, H., Everson, R.M. (eds) Intelligent Data Engineering and Automated Learning – IDEAL 2004. IDEAL 2004. Lecture Notes in Computer Science, vol 3177. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-28651-6_54
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DOI: https://doi.org/10.1007/978-3-540-28651-6_54
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