Name
Title | ||
|---|---|---|
Analyzing high-dimensional multivaríate network links with integrated anomaly detection, highlighting and exploration |
Abstract | ||
|---|---|---|
This paper focuses on the integration of a family of visual analytics techniques for analyzing high-dimensional, multivariate network data that features spatial and temporal information, network connections, and a variety of other categorical and numerical data types. Such data types are commonly encountered in transportation, shipping, and logistics industries. Due to the scale and complexity of the data, it is essential to integrate techniques for data analysis, visualization, and exploration. We present new visual representations, Petal and Thread, to effectively present many-to-many network data including multi-attribute vectors. In addition, we deploy an information-theoretic model for anomaly detection across varying dimensions, displaying highlighted anomalies in a visually consistent manner, as well as supporting a managed process of exploration. Lastly, we evaluate the proposed methodology through data exploration and an empirical study. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/VAST.2014.7042484 | IEEE VAST |
Keywords | Field | DocType |
multivariate network data analysis,integrated anomaly detection,multiattribute vectors,i.3.8 [computer graphics]: applications — visual analytics,visual analytics techniques,data analysis,data exploration,many-to-many network data,information theory,information-theoretic model,i.3.6 [computer graphics]: methodology and techniques — interaction techniques,data visualisation,visual representations,petal and thread,data visualization,high-dimensional multivaríate network links,high-dimensional data analysis,security of data | Anomaly detection,Data mining,Data visualization,Information visualization,Visualization,Computer science,Visual analytics,Interactive visual analysis,Cultural analytics,Analytics | Conference |
ISSN | Citations | PageRank |
2325-9442 | 4 | 0.40 |
References | Authors | |
30 | 9 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sungahn Ko | 1 | 87 | 10.20 |
| Shehzad Afzal | 2 | 65 | 6.94 |
| Simon J. Walton | 3 | 38 | 5.44 |
| Yang Yang | 4 | 181 | 30.09 |
| Junghoon Chae | 5 | 51 | 7.97 |
| Abish Malik | 6 | 84 | 8.88 |
| Yun Jang | 7 | 302 | 25.63 |
| Min Chen | 8 | 1293 | 82.69 |
| David S. Ebert | 9 | 2056 | 232.34 |