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Finding dense subgraphs is an important graph-mining task with many applications. Given that the direct optimization of edge density is not meaningful, as even a single edge achieves maximum density, research has focused on optimizing alternative density functions. A very popular among such functions is the average degree, whose maximization leads to the(More)
We study a novel clustering problem in which the pairwise relations between objects are <i>categorical</i>. This problem can be viewed as clustering the vertices of a graph whose edges are of different types (<i>colors</i>). We introduce an objective function that aims at partitioning the graph such that the edges within each cluster have, as much as(More)
Core decomposition has proven to be a useful primitive for a wide range of graph analyses. One of its most appealing features is that, unlike other notions of dense subgraphs, it can be computed linearly in the size of the input graph. In this paper we provide an analogous tool for uncertain graphs, i.e., graphs whose edges are assigned a probability of(More)
Uncertain, or probabilistic, graphs have been increasingly used to represent noisy linked data in many emerging application scenarios , and have recently attracted the attention of the database research community. A fundamental problem on uncertain graphs is reliability, which deals with the probability of nodes being reach-able one from another. Existing(More)
In recent years there has been a growing interest in clustering uncertain data. In contrast to traditional, "sharp" data representation models, uncertain data objects can be represented in terms of an uncertainty region over which a probability density function (pdf) is defined. In this context, the focus has been mainly on partitional and density-based(More)
Finding dense subgraphs in large graphs is a key primitive in a variety of real-world application domains, encompassing social network analytics, event detection, biology, and finance. In most such applications, one typically aims at finding several (possibly overlapping) dense subgraphs which might correspond to communities in social networks or(More)
A considerable amount of work has been done in data clustering research during the last four decades, and a myriad of methods has been proposed focusing on different data types, proximity functions, cluster representation models, and cluster presentation. However, clustering remains a challenging problem due to its ill-posed nature: it is well known that(More)
PURPOSE Hepatic steatosis is frequently observed in subjects with metabolic syndrome (MS). In type 2 diabetics, it is independently associated with cardiovascular diseases. In order to confirm and extend this finding, a large group of patients with risk factors for atherosclerosis was studied. METHODS Carotid atherosclerosis was investigated by(More)