Abstract
There have been many approaches used to discover useful information patterns from databases, such as concept description, associations, sequential patterns, classification, clustering, and deviation detection. This paper proposes a new type of information pattern, called a typical pattern, which is a small subset of objects selected from a large dataset that provides a compact and suitable representation of the original dataset. The Typical Patterns Mining (TPM) algorithm is developed to mine typical patterns from databases. Extensive experiments are carried out using a real dataset to demonstrate the usefulness of typical patterns in practical situations. The experimental results indicate that TPM is a computationally efficient method and that typical patterns can provide a compact and suitable representation of the original dataset. © 2008 Elsevier Inc. All rights reserved.
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Hu, H. L., & Chen, Y. L. (2008). Mining typical patterns from databases. Information Sciences, 178(19), 3683–3696. https://doi.org/10.1016/j.ins.2008.05.036
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