Real networks exhibit heterogeneous nature with nodes playing far different roles in
structure and function. To identify vital nodes is thus very significant, allowing us to control …

In last two decades, various monitoring systems have been designed and deployed in urban
environments, toward the realization of the so called smart cities. Such systems are based …

Influence maximization (IM) is formulated as selecting a set of initial users from a social
network to maximize the expected number of influenced users. Researchers have made …

With the boom in technologies and mobile networks in recent years, online social networks
have become an integral part of our daily lives. These virtual networks connect people …

Influence Maximization (IM), which selects a set of k users (called seed set) from a social
network to maximize the expected number of influenced users (called influence spread), is a …

Deep learning has yielded state-of-the-art performance on many natural language
processing tasks including named entity recognition (NER). However, this typically requires …

Questions of 'how best to acquire data'are essential to modelling and prediction in the
natural and social sciences, engineering applications, and beyond. Optimal experimental …

Given a social network G and a positive integer k, the influence maximization problem asks
for k nodes (in G) whose adoptions of a certain idea or product can trigger the largest …

Complementary to the fancy applications of social networks, influence analysis is an
indispensable technique supporting these practical applications. In recent years, this …

Given a social network G and a constant k, the influence maximization problem asks for k
nodes in G that (directly and indirectly) influence the largest number of nodes under a pre …