We develop an abstract model of information acquisition from redundant data. We assume a random sampling process from data which contain information with bias and are interested in...
Frequent coherent subgraphscan provide valuable knowledgeabout the underlying internal structure of a graph database, and mining frequently occurring coherent subgraphs from large...
Zhiping Zeng, Jianyong Wang, Lizhu Zhou, George Ka...
Random sampling is one of the most fundamental data management tools available. However, most current research involving sampling considers the problem of how to use a sample, and...
We propose a novel stochastic graph matching algorithm based on data-driven Markov Chain Monte Carlo (DDMCMC) sampling technique. The algorithm explores the solution space efficien...
— Considerable attention has been focused on the properties of graphs derived from Internet measurements. Router-level topologies collected via traceroute-like methods have led s...
Anukool Lakhina, John W. Byers, Mark Crovella, Pen...