Detecting Vehicular Patterns Using a Graph-Based Approach

被引：0

作者：

Velampalli, Sirisha ^{[1
]}

Mookiah, Lenin ^{[2
]}

Eberle, William ^{[2
]}

机构：

[1] Jawaharlal Nehru Technol Univ, Hyderabad, Telangana, India

[2] Tennessee Technol Univ, Cookeville, TN 38505 USA

来源：

2017 IEEE CONFERENCE ON VISUAL ANALYTICS SCIENCE AND TECHNOLOGY (VAST) | 2017年

关键词：

knowledge; graph-based knowledge discovery; graph based anomaly detection;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In the VAST 2017 competition, one of the challenges is to discover vehicular traffic patterns for understanding the reasons behind a decrease in the number of nesting pairs of Rose-Crested Blue Pipit. In this work, we present a graph-based approach that analyzes the data for structural patterns in the data. Our approach first reports the normative patterns in the data, and then discovers any anomalous patterns associated with the previously discovered patterns.

引用

页码：209 / 210

页数：2