Information enhancement for data mining

for further processing. Indeed, information enhancement, which straddles data preprocessing and data mining, often presents itself as a less glamorous but more critical step than other steps in data mining applications; a minor information enhancement adjustment could bring higher effectiveness. Therefore, information enhancement is a crucial research topic. However, much work in relevant fields, such as data mining, is based only on quality data. That is, researchers have been assuming that the input to the data mining algorithms conforms to well-defined data distribution, containing no missing, inconsistent, or incorrect values.1 This leaves a large gap between the available data and the machinery available to process the data.