Urban Anomaly Analytics: Description, Detection, and Prediction

Pattern and Anomaly Detection in Urban Temporal Networks

Broad spectrum of urban activities including mobility can be modeled as temporal networks evolving over time. Abrupt changes in urban dynamics caused by events such as disruption of civic operations, mass crowd gatherings, holidays and natural disasters are potentially reflected in these temporal mobility networks. Identification and early detecting of such abnormal developments is of critical importance for transportation planning and security. Anomaly detection from high dimensional network data is a challenging task as edge level measurements often have low values and high variance resultin…

Graph Learning for Anomaly Analytics: Algorithms, Applications, and Challenges

Anomaly analytics is a popular and vital task in various research contexts, which has been studied for several decades. At the same time, deep learning has shown its capacity in solving many graph-based tasks like, node classification, link prediction, and graph classification. Recently, many studies are extending graph learning models for solving anomaly analytics problems, resulting in beneficial advances in graph-based anomaly analytics techniques. In this survey, we provide a comprehensive overview of graph learning methods for anomaly analytics tasks. We classify them into four categories…

城市异常：一个带有注入异常的模拟人类移动数据集

Urban Anomalies: A Simulated Human Mobility Dataset with Injected Anomalies

本文针对人类移动异常检测缺乏公开数据集的问题，利用 Urban Patterns of Life Simulation 构建了包含四种异常行为和三种注入方法的模拟移动数据集，为基于位置的异常检测模型训练与评估提供了带真实标签的数据支持。

Urban Analytics: Multiplexed and Dynamic Community Networks

In the past decade, cities have experienced rapid growth, expansion, and changes in their community structure. Many aspects of critical urban infrastructure are closely coupled with the human communities that they serve. Urban communities are composed of a multiplex of overlapping factors which can be distinguished into cultural, religious, social-economic, political, and geographical layers. In this paper, we review how increasingly available heterogeneous mobile big data sets can be leveraged to detect the community interaction structure using natural language processing and machine learning…

城市服务关键指标的数据分析及用于领导与决策的仪表板

Data analytics on key indicators for the city's urban services and dashboards for leadership and decision-making

本文探讨了数据分析与仪表板在智慧城市决策中的作用，提出通过整合实时数据流与站点分析的城市仪表板方案，以获取准确信息并提升城市服务可持续性。

TA-Dash: An Interactive Dashboard for Spatial-Temporal Traffic Analytics -- Demo Paper

In recent years, a large number of research efforts aimed at the development of machine learning models to predict complex spatial-temporal mobility patterns and their impact on road traffic and infrastructure. However, the utility of these models is often diminished due to the lack of accessible user interfaces to view and analyse prediction results. In this paper, we present the Traffic Analytics Dashboard ( TA-Dash), an interactive dashboard that enables the visualisation of complex spatial-temporal urban traffic patterns. We demonstrate the utility of TA-Dash at the example of two recently…