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University of Illinois at Urbana-Champaign
*Multidimensional Analysis of Moving Object Data
Abstract
dc:descriptionTo this end, we present our studies in this thesis. With regards to anomaly detection, we present three models to automatically detect moving object anomaly, traffic anomaly, and subspace anomaly. The last of which detects anomalies in a multidimensional space, which is often the case in real world datasets. Additionally, we also address problems that could occur due to sampling in a multidimensional space and how to summarize moving object trajectories for more efficient processing.
Degree
thesis:*- Name thesis:degree_name
- Ph.D.
- Level thesis:degree_level
- Dissertation
- Discipline thesis:degree_discipline
- Computer Science
- Grantor
- University of Illinois at Urbana-Champaign
- Year dc:date
- 2015
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Li, Xiaolei
- Contributors dc:contributor
-
- Han, Jiawei
Subjects
dc:subject × 1Rights
- Language dc:language
- eng
Identifiers
dc:identifier.*- Identifier
- (MiAaPQ)AAI3314964
- OAI identifier oai:identifier
- oai:www.ideals.illinois.edu:2142/81818