Data Mining in Inconsistent Data

Inconsistent research on data mining based on rough set theory focuses on how to deal with the problems caused by inconsistent data and how to increase the adaptability of data mining system by inconsistent data. We propose a hypothesis that some inconsistent data are likely to contain important knowledge easily neglected. By analyzing the causes of inconsistent data, we point out some inconsistent data is generated for knowledge changes caused by environmental changes. Two algorithms are proposed to obtain some knowledge what is easily neglected by adding time or space attributes. The experiments prove that time and space changes can induce changes in knowledge.