In this paper, we consider the problem of mining the special properties of a given record in a relational dataset. In our formulation, a property is a combination of multiple attribute-value pairs. The support of a property is the number of records that satisfy it. We consider a property as special if its support occurs to us as a shock and the measure of this shock factor is more than a user defined threshold η. We provide a way to define this notion of shock based on entropy. We also output the shock factor for records in the dataset in a convenient, easily-interpretable manner. An illustrated example is provided on how users can interpret the results. Experiments on real and synthetic data sets reveal interesting properties of data records that cannot be mined using traditional approaches. © 2010 Springer-Verlag.
CITATION STYLE
Kumar, H., Paravastu, R., & Pudi, V. (2010). Specialty mining. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6263 LNCS, pp. 227–238). https://doi.org/10.1007/978-3-642-15105-7_18
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