Continuous Ranking Queries on Uncertain Streams
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The uncertain data stream model developed in Section 2.3.1 characterizes the dynamic nature of uncertain data. Conceptually, an uncertain data stream contains a set of (potentially) infinite instances. To keep our discussion simple, we assume a synchronous model in this chapter. That is, at each time instant t (t > 0), an instance is collected for an uncertain data stream. A sliding window \( W_w^t \) selects the set of instances collected between time instants t − w and t. The instances of each uncertain data stream in the sliding window can be considered as an uncertain object. We assume that the membership probabilities of all instances are identical. Some of our developed methods can also handle the case of different membership probabilities, which will be discussed in Section 6.5.
KeywordsExact Algorithm Approximation Quality Deterministic Method Query Evaluation Uncertain Object
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