Mining Frequent Itemsets over Recent Data Stream Based on Genetic Algorithm

Data stream is massive sequence of data elements generated at a rapid rate which is characterized by continuously flowing, high arrival rate, unbounded size of data and realtime query requests. The knowledge embedded in a data stream is more likely to be changed as time goes by. Identifying the recent change of a data stream, especially for an online data stream, can provide valuable information for the analysis of the data stream. Frequent patterns on a data stream can provide an important basis for decision making and applications. Because of the data stream’s fluidity and continuity, the information of frequent patterns changes with the new data coming.