Density-based clustering of big probabilistic graphs
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DOI: 10.1007/s12530-018-9223-2
Abstract: Clustering is a machine learning task to group similar objects in coherent sets. These groups exhibit similar behavior with-in their cluster. With the exponential increase in the data volume, robust approaches are required to process… read more here.
Keywords: based clustering; density based; graphs; probabilistic graphs ... See more keywords
An Algorithm for the Myerson Value in Probabilistic Graphs with an Application to Weighted Voting
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DOI: 10.1109/mis.2017.3
Abstract: Myerson's graph-restricted games are a well-known formalism for modeling cooperation that's subject to restrictions. In particular, Myerson considered a coalitional game in which cooperation is possible only through an underlying network of links between agents.… read more here.
Keywords: graph; myerson value; myerson; probabilistic graphs ... See more keywords
Efficient Structural Clustering on Probabilistic Graphs
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Transactions on Knowledge and Data Engineering"
DOI: 10.1109/tkde.2018.2872553
Abstract: Structural clustering is a fundamental graph mining operator which is not only able to find densely-connected clusters, but it can also identify hub vertices and outliers in the graph. Previous structural clustering algorithms are tailored… read more here.
Keywords: efficient structural; clustering probabilistic; probabilistic graphs; structural clustering ... See more keywords