Most real-world data are scattered across different companies or government organizations, and cannot be easily integrated under data privacy and related regulations such as the European Union’s General Data Protection Regulation (GDPR) and Chin…
Knowledge graphs have received intensive research interests. When the labels of most nodes or datapoints are missing, anchor graph and hierarchical anchor graph models can be employed. With an anchor graph or hierarchical anchor graph, we only need to …
Web advertising related to Human Trafficking (HT) activity has been on the rise in recent years. Answering entity-centric questions over crawled HT Web corpora to assist investigators in the real world is an important social problem, involving many tec…
Community detection is a fundamental task in graph data mining. Most existing studies in contact networks, collaboration networks, and social networks do not utilize the temporal information associated with edges for community detection. In this articl…
Urban anomalies may result in loss of life or property if not handled properly. Automatically alerting anomalies in their early stage or even predicting anomalies before happening is of great value for populations. Recently, data-driven urban anomaly a…
For the pursuit of ubiquitous computing, distributed computing systems containing the cloud, edge devices, and Internet-of-Things devices are highly demanded. However, existing distributed frameworks do not tailor for the fast development of Deep Neura…
Internet of Things (IoT) connects physical, cyber and human spaces. Event-based system is one of the cornerstones to help IoT achieve real-time monitoring, context-awareness and intelligent control. In the era of big data, the huge amount and high comp…
Link prediction over a knowledge graph aims to predict the missing head entities $h$h or tail entities $t$t and missing relations $r$r for a triple $(h,r,t)$(h,r,t). Recent years have witnessed great advance of knowledge graph embedding based link pred…
Entity Set Expansion (ESE) is the problem that expands a small set of seed entities into a more complete set, entities of which have common traits. As a popular data mining task, ESE has been widely used in many applications, such as dictionary constru…
In this big data era, knowledge becomes increasingly linked, along with the rapid growth in data volume. Connected knowledge is naturally represented and stored as knowledge graphs, which are of more and more importance for many frontier research areas…