Concept Change Aware Dynamic Sliding Window Based Frequent Itemsets Mining Over Data Streams
نویسندگان
چکیده
Considering the continuity of a data stream, the accessed windows information of a data stream may not be useful as a concept change is effected on further data. In order to support frequent item mining over data stream, the interesting recent concept change of a data stream needs to be identified flexibly. Based on this, an algorithm can be able to identify the range of the further window. A method for finding frequent itemsets over a data stream based on a sliding window has been proposed here, which finds the interesting further range of frequent itemsets by the concept changes observed in recent windows.
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