Mining Approximate Frequent Itemsets over Data Streams

Abstract

This paper proposes a method based on Lossy Counting to mine frequent itemsets. Logarithmic tilted time window is adopted to emphasize the importance of recent data. Multilayer count queue framework is used to avoid the counter overflowing and query top-Kitemsets quickly using a index table.