EnsembleLens: Ensemble-based Visual Exploration of Anomaly Detection Algorithms with Multidimensional Data
EnsembleLens: Ensemble-based Visual Exploration of Anomaly Detection Algorithms with Multidimensional Data
复制标题
EnsembleLens：基于集成的多维数据异常检测算法的视觉探索
DOI：
10.1109/tvcg.2018.2864825
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发表时间：
2019-01
影响因子：
5.2
通讯作者：
Cao Nan
中科院分区：
文献类型：
--
作者：
Xu Ke;Xia Meng;Mu Xing;Wang Yun;Cao Nan
The results of anomaly detection are sensitive to the choice of detection algorithms as they are specialized for different properties of data, especially for multidimensional data. Thus, it is vital to select the algorithm appropriately. To systematically select the algorithms, ensemble analysis techniques have been developed to support the assembly and comparison of heterogeneous algorithms. However, challenges remain due to the absence of the ground truth, interpretation, or evaluation of these anomaly detectors. In this paper, we present a visual analytics system named EnsembleLens that evaluates anomaly detection algorithms based on the ensemble analysis process. The system visualizes the ensemble processes and results by a set of novel visual designs and multiple coordinated contextual views to meet the requirements of correlation analysis, assessment and reasoning of anomaly detection algorithms. We also introduce an interactive analysis workflow that dynamically produces contextualized and interpretable data summaries that allow further refinements of exploration results based on user feedback. We demonstrate the effectiveness of EnsembleLens through a quantitative evaluation, three case studies with real-world data and interviews with two domain experts.
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DOI：
10.1109/wsc.2007.4419664
发表时间：
2007-12
期刊：
2007 Winter Simulation Conference
影响因子：
--
作者：
T. Nocke;M. Flechsig;U. Böhm
通讯作者：
T. Nocke;M. Flechsig;U. Böhm
影响因子：
12
作者：
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通讯作者：
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DOI：
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发表时间：
2016-07
期刊：
ArXiv
影响因子：
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作者：
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通讯作者：
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DOI：
10.1145/3097983.3098154
发表时间：
2017-05
期刊：
Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
影响因子：
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作者：
Yanjie Fu;C. Aggarwal;S. Parthasarathy;D. Turaga;Hui Xiong
通讯作者：
Yanjie Fu;C. Aggarwal;S. Parthasarathy;D. Turaga;Hui Xiong
DOI：
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发表时间：
2003-08
期刊：
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影响因子：
--
作者：
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通讯作者：
Weng-Keen Wong;A. Moore;G. Cooper;M. Wagner