Non-match research involves studying the aspects of data in which there is not a direct correspondence or similarity between different elements. This can include studying outliers, anomalies, and discrepancies in data sets, as well as exploring patterns or relationships that may not be immediately apparent. Non-match research can be used in various fields such as data analysis, statistics, and machine learning to identify irregularities and uncover hidden insights in data.