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Link prediction is a popular research area with important applications in a variety of disciplines, including biology, social science, security, and medicine. The fundamental requirement of link prediction is the accurate and effective prediction of new links in networks. While there are many different methods proposed for link prediction, we argue that the(More)
Demographics are widely used in marketing to characterize different types of customers. However, in practice, demographic information such as age, gender, and location is usually unavailable due to privacy and other reasons. In this paper, we aim to harness the power of big data to automatically infer users' demographics based on their daily mobile(More)
—Link prediction is an important task in network analysis, benefiting researchers and organizations in a variety of fields. Many networks in the real world, for example social networks, are heterogeneous, having multiple types of links and complex dependency structures. Link prediction in such networks must model the influence propagating between(More)
—Link prediction is an important task in network analysis, benefiting researchers and organizations in a variety of fields. Many networks in the real world, for example social networks, are heterogeneous, having multiple types of links and complex dependence structures. Link prediction in such networks must model the influence propagating between(More)
In the past few years exciting advances in the development of pervasive computing technologies have taken place, in particular the field of flexible electronics is emerging: electronic components such as transistors and wires can be built on a thin flexible material, and polymer wires can be made to be flexible and durable. These technologies offer the(More)
An underlying assumption of biomedical informatics is that decisions can be more informed when professionals are assisted by analytical systems. For this purpose, we propose ALIVE, a multi-relational link prediction and visualization environment for the healthcare domain. ALIVE combines novel link prediction methods with a simple user interface and(More)
—Community detection or cluster detection in networks is a well-studied, albeit hard, problem. Given the scale and complexity of modern day social networks, detecting " reasonable " communities is an even harder problem. Since the first use of k-means algorithm in 1960s, many community detection algorithms have been invented-most of which are developed with(More)
The understanding of how humans move is a longstanding challenge in the natural science. An important question is, to what degree is human behavior predictable? The ability to foresee the mobility of humans is crucial from predicting the spread of human to urban planning. Previous research has focused on predicting individual mobility behavior, such as the(More)
Collaboration is an integral element of the scientific process that often leads to findings with significant impact. While extensive efforts have been devoted to quantifying and predicting research impact, the question of how collaborative behavior influences scientific impact remains unaddressed. In this work, we study the interplay between scientists'(More)
BACKGROUND Archaeological studies have revealed a series of cultural changes around the Last Glacial Maximum in East Asia; whether these changes left any signatures in the gene pool of East Asians remains poorly indicated. To achieve deeper insights into the demographic history of modern humans in East Asia around the Last Glacial Maximum, we extensively(More)