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• W770061668 abstract "Previous chapter Next chapter Full AccessProceedings Proceedings of the 2013 SIAM International Conference on Data Mining (SDM)Mining Connection Pathways for Marked Nodes in Large GraphsLeman Akoglu, Duen Horng Chau, Jilles Vreeken, Nikolaj Tatti, Hanghang Tong, and Christos FaloutsosLeman Akoglu, Duen Horng Chau, Jilles Vreeken, Nikolaj Tatti, Hanghang Tong, and Christos Faloutsospp.37 - 45Chapter DOI:https://doi.org/10.1137/1.9781611972832.5PDFBibTexSections ToolsAdd to favoritesExport CitationTrack CitationsEmail SectionsAboutAbstract Suppose we are given a large graph in which, by some external process, a handful of nodes are marked. What can we say about these nodes? Are they close together in the graph? or, if segregated, how many groups do they form? We approach this problem by trying to find sets of simple connection pathways between sets of marked nodes. We formalize the problem in terms of the Minimum Description Length principle: a pathway is simple when we need only few bits to tell which edges to follow, such that we visit all nodes in a group. Then, the best partitioning is the one that requires the least number of bits to describe the paths that visit all the marked nodes. We prove that solving this problem is NP-hard, and introduce DOT2DOT, an efficient algorithm for partitioning marked nodes by finding simple pathways between nodes. Experimentation shows that DOT2DOT correctly groups nodes for which good connection paths can be constructed, while separating distant nodes. Previous chapter Next chapter RelatedDetails Published:2013ISBN:978-1-61197-262-7eISBN:978-1-61197-283-2 https://doi.org/10.1137/1.9781611972832Book Series Name:ProceedingsBook Code:PRDT13Book Pages:1-804" @default.
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• W770061668 date "2013-05-02" @default.
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• W770061668 title "Mining Connection Pathways for Marked Nodes in Large Graphs" @default.
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