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Efficiently Indexing Shortest Paths by Exploiting Symmetry in Graphs
 In EDBT 2009
"... Shortest path queries (SPQ) are essential in many graph analysis and mining tasks. However, answering shortest path queries onthefly on large graphs is costly. To online answer shortest path queries, we may materialize and index shortest paths. However, a straightforward index of all shortest path ..."
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Cited by 16 (2 self)
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Shortest path queries (SPQ) are essential in many graph analysis and mining tasks. However, answering shortest path queries onthefly on large graphs is costly. To online answer shortest path queries, we may materialize and index shortest paths. However, a straightforward index of all shortest paths in a graph of N vertices takes O(N 2) space. In this paper, we tackle the problem of indexing shortest paths and online answering shortest path queries. As many large real graphs are shown richly symmetric, the central idea of our approach is to use graph symmetry to reduce the index size while retaining the correctness and the efficiency of shortest path query answering. Technically, we develop a framework to index a large graph at the orbit level instead of the vertex level so that the number of breadthfirst
kSymmetry model for identity anonymization in social networks
 In EDBT
, 2010
"... With more and more social network data being released, protecting the sensitive information within social networks from leakage has become an important concern of publishers. Adversaries with some background structural knowledge about a target individual can easily reidentify him from the network, ..."
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Cited by 11 (0 self)
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With more and more social network data being released, protecting the sensitive information within social networks from leakage has become an important concern of publishers. Adversaries with some background structural knowledge about a target individual can easily reidentify him from the network, even if the identifiers have been replaced by randomized integers(i.e., the network is naivelyanonymized). Since there exists numerous topological information that can be used to attack a victim’s privacy, to resist such structural reidentification becomes a great challenge. Previous works only investigated a minority of such structural attacks, without considering protecting against reidentification under any potential structural knowledge about a target. To achieve this objective, in this paper we propose
Relations Between Graphs
, 2010
"... Given two graphs G = (VG, EG) and H = (VH, EH), we ask under which conditions there is a relation R ⊆ VG × VH that generates the edges of H given the structure of the graph G. This construction can be seen as a form of multihomomorphism. It generalizes surjective homomorphisms of graphs and natural ..."
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Given two graphs G = (VG, EG) and H = (VH, EH), we ask under which conditions there is a relation R ⊆ VG × VH that generates the edges of H given the structure of the graph G. This construction can be seen as a form of multihomomorphism. It generalizes surjective homomorphisms of graphs and naturally leads to notions of Rretractions, Rcores, and Rcocores of graphs. Both Rcores and Rcocores of graphs are unique up to isomorphism and can be computed in polynomial time.
Algebraic and Topological Indices of Molecular Pathway Networks in Human Cancers
, 2014
"... Proteinprotein interaction networks associated with diseases have gained prominence as an area of research. We investigate algebraic and topological indices for proteinprotein interaction networks of 11 human cancers derived from the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. We find ..."
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Proteinprotein interaction networks associated with diseases have gained prominence as an area of research. We investigate algebraic and topological indices for proteinprotein interaction networks of 11 human cancers derived from the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. We find a strong correlation between relative automorphism group sizes and topological network complexities on the one hand and five year survival probabilities on the other hand. Moreover, we identify several protein families (e.g. PIK, ITG, AKT families) that are repeated motifs in many of the cancer pathways. Interestingly, these sources of symmetry are often central rather than peripheral. Our results can aide in identification of promising targets for anticancer drugs. Beyond that, we provide a unifying framework to study proteinprotein interaction networks of families of related diseases (e.g. neurodegenerative diseases, viral diseases, substance abuse disorders).
Article Complex Networks and Symmetry II: Reciprocity and Evolution of World Trade
, 2010
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