A Weighted Frequent Set Item Mining For Intelligent Decision In Smart Systems

A Weighted Frequent Item set Mining Algorithm for Intelligent Decision in Smart Systems

Abstract:-

Intelligent decision is the key technology of smart systems. Data mining technology has been playing an increasingly important role in decision making activities. Frequent item set mining, as an important step of association rule analysis, is becoming one of the most important research fields in data mining. Weighted frequent item set mining in uncertain databases should take both the existential probability and importance of items into account in order to find frequent item sets of great importance to users. However, the introduction of weight makes the weighted frequent item sets not satisfy the downward closure property any longer. As a result, the search space of frequent item sets cannot be narrowed according to downward closure property which leads to a poor time efficiency. In this paper, the weight judgment downward closure property for weighted frequent item sets and the existence property of weighted frequent subsets are introduced and proved first. Based on these two properties, the WD-FIM (Weight judgment Downward closure property based Frequent Item set Mining) algorithm is proposed to narrow the searching space of weighted frequent item sets and improve the time efficiency. Moreover, the completeness and time efficiency of WD-FIM algorithm are analysed theoretically. Finally, the performance of the proposed WD-FIM algorithm is verified on both synthetic and real-life datasets.