By JIN CHEQING & ZHOU AOYING,Aoying Zhou

Data uncertainty broadly exists in lots of functions, and an doubtful info move is a chain of doubtful tuples that arrive quickly. in spite of the fact that, conventional recommendations for deterministic info streams can't be utilized to house info uncertainty at once a result of exponential progress of attainable answer space.

This ebook offers a finished evaluation of the authors' paintings on querying and mining doubtful information streams. Its contents comprise a few very important discoveries facing ordinary subject matters resembling top-k question, ER-Topk question, rarity estimation, set similarity, and clustering.

Querying and Mining doubtful information Streams is written for pros, researchers, and graduate scholars in info mining and its a variety of comparable fields.

Contents:

  • Introduction
  • Top-k Queries Over the Sliding-window Model
  • ER-Topk question Over the Landmark Model
  • Rarity Estimation
  • Set Similarity
  • Clustering
  • Conclusion

Readership: scholars and pros fascinated about information mining, mammoth facts, and knowledge gathering.
Key Features:

  • The first ebook on doubtful info flow management
  • There exist major contributions on regular topics

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