Article ID Journal Published Year Pages File Type
379196 Data & Knowledge Engineering 2007 15 Pages PDF
Abstract

A variety of cluster analysis techniques exist to group objects having similar characteristics. However, the implementation of many of these techniques is challenging due to the fact that much of the data contained in today’s databases is categorical in nature. While there have been recent advances in algorithms for clustering categorical data, some are unable to handle uncertainty in the clustering process while others have stability issues. This research proposes a new algorithm for clustering categorical data, termed Min–Min-Roughness (MMR), based on Rough Set Theory (RST), which has the ability to handle the uncertainty in the clustering process.

Related Topics
Physical Sciences and Engineering Computer Science Artificial Intelligence
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