DSTree: A Tree Structure for the Mining of Frequent Sets from Data Streams

With advances in technology, a flood of data can be produced in many applications such as sensor networks and Web click streams. This calls for efficient techniques for extracting useful information from streams of data. In this paper, we propose a novel tree structure, called DSTree (Data Stream Tree), that captures important data from the streams. By exploiting its nice properties, the DSTree can be easily maintained and mined for frequent itemsets as well as various other patterns like constrained itemsets.