Data set frequent item set mining availability evaluation method

The invention discloses a data set frequent item set mining availability evaluation method, which comprises the following steps of: (1) setting C = {I1, I2,..., In} as a set of items, giving transaction data sets D1 and D2, and mining D1 and D2 by utilizing an Apriori algorithm to obtain maximum frequent item set sets, and recording the maximum frequent item set sets as FIS1 and FIS2; (2) any item set MIS1 of the FIS1 and any item set MIS2 of the FIS2 are matched through an item set matching algorithm F, a paired item set table Pairs is obtained, the Pairs is composed of item set pairs < MIS1, MIS2 and score1 >, score1 represents the item similarity of the MIS1 and the MIS2, and the item similarity of the MIS1 and the MIS2 is obtained through calculation in the matching process. (3) for each item < MIS1, MIS2, score 1 > in the Pairs, calculating the support degree similarity score 2 of the MIS1 and the MIS2, further calculating to obtain the composite similarity score of the MIS1 and the MIS2, and updating th