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Continuous Ranking Queries on Uncertain Streams

  • Ming HuaEmail author
  • Jian Pei
Chapter
  • 485 Downloads
Part of the Advances in Database Systems book series (ADBS, volume 42)

Abstract

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.

Keywords

Exact Algorithm Approximation Quality Deterministic Method Query Evaluation Uncertain Object 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  1. 1.Facebook Inc.Palo Alto CaliforniaUSA
  2. 2.School of Computing ScienceSimon Fraser UniversityBurnaby BritishCanada

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