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So many applications of data streams in the world where the people require association rule mining, like network intrusion detection, sensor network, financial monitoring, web click streams analysis and network traffic monitoring. Data streams are different from traditional static databases This thing raises new problems that need to be considered when developing association rule mining techniques for streams data. In this paper, the authors discuss those problems and how they addressed in the existing literature. Data streams are ordered sequences of items that arrive in timely order. Data streams are unbounded, continuous, which are arrive continuously in high speed with large amount of data and distribution of data also changing.
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