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Outlier detection on uncertain data: Objects, instances, and inferences

Publication ,  Conference
Jiang, B; Pei, J
Published in: Proceedings - International Conference on Data Engineering
June 6, 2011

This paper studies the problem of outlier detection on uncertain data. We start with a comprehensive model considering both uncertain objects and their instances. An uncertain object has some inherent attributes and consists of a set of instances which are modeled by a probability density distribution. We detect outliers at both the instance level and the object level. To detect outlier instances, it is a prerequisite to know normal instances. By assuming that uncertain objects with similar properties tend to have similar instances, we learn the normal instances for each uncertain object using the instances of objects with similar properties. Consequently, outlier instances can be detected by comparing against normal ones. Furthermore, we can detect outlier objects most of whose instances are outliers. Technically, we use a Bayesian inference algorithm to solve the problem, and develop an approximation algorithm and a filtering algorithm to speed up the computation. An extensive empirical study on both real data and synthetic data verifies the effectiveness and efficiency of our algorithms. © 2011 IEEE.

Duke Scholars

Published In

Proceedings - International Conference on Data Engineering

DOI

ISSN

1084-4627

ISBN

9781424489589

Publication Date

June 6, 2011

Start / End Page

422 / 433
 

Citation

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MLA
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Jiang, B., & Pei, J. (2011). Outlier detection on uncertain data: Objects, instances, and inferences. In Proceedings - International Conference on Data Engineering (pp. 422–433). https://doi.org/10.1109/ICDE.2011.5767850
Jiang, B., and J. Pei. “Outlier detection on uncertain data: Objects, instances, and inferences.” In Proceedings - International Conference on Data Engineering, 422–33, 2011. https://doi.org/10.1109/ICDE.2011.5767850.
Jiang B, Pei J. Outlier detection on uncertain data: Objects, instances, and inferences. In: Proceedings - International Conference on Data Engineering. 2011. p. 422–33.
Jiang, B., and J. Pei. “Outlier detection on uncertain data: Objects, instances, and inferences.” Proceedings - International Conference on Data Engineering, 2011, pp. 422–33. Scopus, doi:10.1109/ICDE.2011.5767850.
Jiang B, Pei J. Outlier detection on uncertain data: Objects, instances, and inferences. Proceedings - International Conference on Data Engineering. 2011. p. 422–433.

Published In

Proceedings - International Conference on Data Engineering

DOI

ISSN

1084-4627

ISBN

9781424489589

Publication Date

June 6, 2011

Start / End Page

422 / 433