Abstract: A pattern recognition method applicable to unique associated pattern recognition in a structured information system or structured database is presented. The process may be used to find patterns in a column which are associated with unique data values in another column, or to find the number of unique values in the second column which are paired with the same associated pattern in the first column. The technique is easily extended to more general cases in which both the condition field and the associated pattern field may be two groups of fields.

Abstract: By placing a low cardinality node or a leaf in a lower level, and a high cardinality node or a leaf at a higher level, an optimal memory structure is automatically generated which yields the best compression within N-gram technology. After making an initial list of parallel streams or fields, the streams are ordered in accordance with increasing cardinality. Adjacent streams (fields), or nodes, are paired, and the children of the resulting node are eliminated from the list, while a new parent node is added to the list. The resulting new list is re-arranged from right to left as a function of increasing cardinality, and the pairing steps are repeated until a single root node is remains for the final memory structure.