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—Power networks and information systems become more and more interdependent to ensure better supports for the functionality as well as improve the economy. However, power networks also tend to be more vulnerable due to the cascading failures from their interdependent information systems, i.e., the failures in the information systems can cause the failures(More)
Online social networks (OSNs) have become one of the most effective channels for marketing and advertising. Since users are often influenced by their friends, "word-of-mouth" exchanges so-called viral marketing in social networks can be used to increases product adoption or widely spread content over the network. The common perception of viral marketing(More)
We propose DOCA (Detecting Overlapping Community Algorithm), a connection-based algorithm for discovering high quality overlapping community structures in social networks. Our proposed method is fast, very limited parameter dependent and only requires local knowledge about the network topology. Furthermore, the community structures discovered by DOCA are(More)
In social networks, there is a tendency for connected users to match each other's behaviors. Moreover, a user likely adopts a behavior, if a certain fraction of his family and friends follows that behavior. Identifying people who have the most influential effect to the others is of great advantages, especially in politics, marketing, behavior correction,(More)
We describe a new algorithm, Minesweeper, that is able to satisfy stronger runtime guarantees than previous join algorithms (colloquially ``beyond worst-case'' guarantees) for data in indexed search trees. Our first contribution is developing a framework to measure this stronger notion of complexity, which we call "certificate complexity," that extends(More)
Join optimization has been dominated by Selinger-style, pairwise optimizers for decades. But, Selinger-style algorithms are asymptotically suboptimal for applications in graphic analytics. This sub-optimality is one of the reasons that many have advocated supplementing relational engines with specialized graph processing engines. Recently, new join(More)
—Online Social Networks (OSNs) have recently emerged as one of the most effective channels for information sharing and discovery due to their ability of allowing users to read and create new content simultaneously. While this advantage provides users more rooms to decide which content to follow, it also makes OSNs fertile grounds for the wide spread of(More)
The discovery of power law distribution in degree sequence (i.e. the number of vertices with degree i is proportional to i −β for some constant β) of many large-scale real networks creates a belief that it may be easier to solve many optimization problems in such networks. Our works focus on the hardness and inapproximability of optimization problems on(More)
The least cost influence (LCI) problem, which asks to identify a minimum number of seed users who can eventually influence a large number of users, has become one of the central research topics recently in online social networks (OSNs). However, existing works mostly focused on a single network while users nowadays often join several OSNs. Thus, it is(More)