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…
Complex data mining algorithms are processed in multiple iterations, where output of one iteration is used as input for the subsequent iterations. Existing parallel programming frameworks, e.g., MapReduce, Pregel and Spark, adopt the breadth first sear…
Attributed graphs are widely used to represent network data where the attribute information of nodes is available. To address the problem of identifying clusters in attributed graphs, most of existing solutions are developed simply based on certain par…
Real-life systems involving interacting objects are typically modeled as graphs and can often grow very large in size. Revealing the community structure of such systems is crucial in helping us better understand their complex nature. However, the ever-…
Many applications seek to make sense of high volume streaming data from social media by identifying spatiotemporal patterns. Events, representing topics that emerge and decay over time, are detected by monitoring for changes in the language being used,…
Recent years have witnessed a successful rise of the time synchronized gossiping comment, or so-called danmu combined with online videos. This new business mode has enriched communication among users by sending users’ feelings through danmus and…