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In the era of big data and cloud, distributed key-value stores are increasingly used as building blocks of large-scale applications. Comparing to traditional relational databases, key-value stores are particularly compelling due to their low latency and excellent scalability. Many big companies, such as Facebook and Amazon, run multiple different applications and services on top of a single key-value...
Influence among objects prevalently exists in graph structured data. However, most existing research efforts detect influence among objects from snapshots of homogeneous graphs. In this paper, we study a new problem of detecting time-evolving influence among objects from dynamic heterogeneous graphs. We propose a probabilistic graphical model, Time-evolving Influence Model (TIM), to capture the temporal...
Nodes of a social graph often represent entities with specific labels, denoting properties such as age-group or gender. Design of algorithms to assign labels to unlabeled nodes by leveraging node-proximity and a-priori labels of seed nodes is of significant interest. A semi-supervised approach to solve this problem is termed "LPA-Label Propagation Algorithm" where labels of a subset of nodes...
Finding the number of triangles in a graph (network) is an important problem in graph analysis. The number of triangles also has important applications in graph mining. Big graphs emerging from numerous application areas pose a significant challenge for the analysis and mining since these graphs consist of millions, or even billions, of nodes and edges. Graphs of such scale necessitate the development...
Diffusion processes in networks can be used to model many real-world processes. Analysis of diffusion traces can help us answer important questions such as the source of diffusion and the role of each node in the diffusion process. However, in large-scale networks, it is very expensive if not impossible to monitor the entire network to collect the complete diffusion trace. This paper considers diffusion...
The difficulty of analysis in social networks mainly originates from its huge scale and complicated relations in the network. Social network is a complex system that we can hardly inspect its deep mechanism with only regarding it as a whole. Game theory is a study that focuses on interactions and reactions between intelligent individuals. Recently, game theory based methods are proposed to tackle...
In this paper, we focus on the task of learning influential parameters under unsteady and dynamic environments. Such unsteady and dynamic environments often occur in the ramp-up phase of manufacturing. We propose a novel regularization-based framework, called Distributed Dynamic Elastic Nets (DDEN), for this problem and formulate it as a convex optimization objective. Our approach solves the optimization...
An A-Star algorithm based on-demand routing (ASOR) protocol for hierarchical Low Earth Orbit (LEO)/ Middle Earth Orbit (MEO) satellite networks is proposed and evaluated in this paper. The protocol uses the improved A-Star to decrease the searching area and the computing cost, which is significant for real time data. It also calculates the optimal path on-demand, which can guarantee an optimal path...
In many emerging data mining situations we encounter multiple large binary relational datasets that are generated independently but are semantically interconnected and must be mined simultaneously to obtain an integrated effect of the data residing in all of them. The idea of finding 3-clusters is increasingly used in situations where one has to concurrently mine two distinct datasets that share a...
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