Sliding-Window Top-K Pattern Mining on Uncertain Streams

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Provided by: Binary Information Press
Topic: Data Management
Format: PDF
Top-k pattern mining has been studied extensively in streaming data applications such as web clickstreams, network monitoring and retail store transactions, in which items are precise and certain. However, in many real-time application domains, such as sensor network monitors and mobile object data management, items are streaming continuously and uncertain, this is because in these applications users are uncertain about the absence or presence of the data items. These uncertain streams have attracted a lot of attention very recently. Since large amount of such uncertain streaming data arrive rapidly, there are some inherent challenges for processing such of these data.
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