Patent ID: 8112440

Claim:
A computerized method of identifying relational patterns that exist across a plurality of databases, each of the plurality of databases including one or more records having one or more data items of interest, the method comprising: generating a hybrid frequent pattern tree from one or more records from each of the plurality of databases, the hybrid frequent pattern tree including one or more data node branches having one or more data nodes, each of the one or more data nodes representing one of the one or more data items of interest, the one or more data nodes of each of the one or more data node branches representing data items that are related to each other in records of the plurality of databases, each of the one or more data nodes having the following form: {x|y 1 : . . . :y M }, where M is the number of the plurality of databases, x is a data item indicator for the one of the one or more data items of interest that is represented by the data node, y 1 , . . . , y M are data item support counters indicating the number of times that data item x appears in databases D 1 , . . . , D M , respectively, in relation to other data items represented in the data branch having the data node; and mining the hybrid frequent pattern tree to identify one or more relational patterns that exists across the plurality of databases by considering pattern support data across the plurality of databases at the same time, the pattern support data based on the data item support data for the plurality of databases in the data item support counters of the hybrid frequent pattern tree, wherein said mining includes determining a pattern P including pattern data items and corresponding pattern data item support values derived from the one or more branches where the support for the pattern across the plurality of databases is determined according to: P Sup = { min ⁢ { Sup P ⁡ [ k ] 1 } k = 1 , … ⁢ , K : … : ⁢ min ⁢ { Sup P ⁡ [ k ] M } k = 1 , … ⁢ , K } where Sup P[k] i is the support value of the k th data item in P (with respect to database D i ) and K is the number of items in P, M represents the number of the plurality of databases, D i represents each of the plurality of databases where i=1, . . . , M.