In history research, cohort analysis seeks to identify social structures and figure mobilities by
studying the group-based behavior of historical figures. Prior works mainly employ automatic …

The spatial time series generated by city sensors allow us to observe urban phenomena like
environmental pollution and traffic congestion at an unprecedented scale. However …

Constructing supervised machine learning models for real-world video analysis require
substantial labeled data, which is costly to acquire due to scarce domain expertise and …

How to achieve academic career success has been a long-standing research question in
social science research. With the growing availability of large-scale well-documented …

The efficiency of warehouses is vital to e-commerce. Fast order processing at the
warehouses ensures timely deliveries and improves customer satisfaction. However …

The newest developments in the fields of data analysis, visualization, and predictive
analytics are organized and discussed in this study. The utilization of data to acquire …

Planning an ideal tour schedule is a tedious process, where the attractions to visit and the
order of visits need to be carefully determined. In this paper, we propose a novel interactive …

Event sequence data is a special type of time-dependent data that captures information
about the order in which discrete events occur. The time-dimension is one of the factors that …

Human-centered AI aims to bridge the gap between machine decision-making and human
understanding. However, even for classification tasks where deep neural networks have …

The development of digitized humanity information provides a new perspective on data-
oriented studies of history. Many previous studies have ignored uncertainty in the …