FRIOD: a deeply integrated feature-rich interactive system for effective and efficient outlier detection
Article
Article Title | FRIOD: a deeply integrated feature-rich interactive system for effective and efficient outlier detection |
---|---|
ERA Journal ID | 210567 |
Article Category | Article |
Authors | Zhu, Xiaodong (Author), Zhang, Ji (Author), Li, Hongzhou (Author), Fournier-Viger, Philippe (Author), Lin, Jerry Chun-Wei (Author) and Chang, Liang (Author) |
Journal Title | IEEE Access |
Journal Citation | 5, pp. 25682-25695 |
Article Number | 8101452 |
Number of Pages | 14 |
Year | 2017 |
Publisher | IEEE (Institute of Electrical and Electronics Engineers) |
Place of Publication | United States |
ISSN | 2169-3536 |
Digital Object Identifier (DOI) | https://doi.org/10.1109/ACCESS.2017.2771237 |
Web Address (URL) | https://ieeexplore.ieee.org/document/8101452 |
Abstract | In this paper, we propose an novel interactive outlier detection system called feature-rich interactive outlier detection (FRIOD), which features a deep integration of human interaction to improve detection performance and greatly streamline the detection process. A user-friendly interactive mechanism is developed to allow easy and intuitive user interaction in all the major stages of the underlying outlier detection algorithm which includes dense cell selection, location-aware distance thresholding, and final top outlier validation. By doing so, we can mitigate the major difficulty of the competitive outlier detection methods in specifying the key parameter values, such as the density and distance thresholds. An innovative optimization approach is also proposed to optimize the grid-based space partitioning, which is a critical step of FRIOD. Such optimization fully considers the high-quality outliers it detects with the aid of human interaction. The experimental evaluation demonstrates that FRIOD can improve the quality of the detected outliers and make the detection process more intuitive, effective, and efficient. |
Keywords | human interaction, outlier detection, space partitioning visualization |
ANZSRC Field of Research 2020 | 469999. Other information and computing sciences not elsewhere classified |
Byline Affiliations | Nanjing University of Information Science and Technology, China |
School of Agricultural, Computational and Environmental Sciences | |
Guilin University of Electronic Technology, China | |
Harbin Institute of Technology, China | |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q52w0/friod-a-deeply-integrated-feature-rich-interactive-system-for-effective-and-efficient-outlier-detection
Download files
150
total views94
total downloads0
views this month0
downloads this month