large graph
Survey on Large Graph Analysis and Visualization
... summarising large graph. GMine introduceses the concept of super graph ,Graph tree and CEPS ...sub graph ,it contains collection of paths connecting sub graph of ...query ...
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Large Graph mining Approach for Cluster Analysis to Identify Critical Components within the Water Distribution System
... of large graphs can be categorized into two ways, topological and attributed ...many graph clustering algorithms that mainly focus on the topological structure for clustering but these approaches ignore the ...
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Subgraph Matching with Set Similarity in a Large Graph Database
... a large scale graph. GraphQL is a query language for graph databases which supports graphs as the basic unit of ...utilized graph exploration and parallel computing to process subgraph ...
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Subgraph Mining of Seminal Papers in a Large Graph with Their Paper Genealogy
... pattern graph in a very target graph for this some algorithms are applied which is useful to remove unsuccessful mapping which retrieves sub graphs that are structurally similarity to the query ...
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Enumerating Maximal Bicliques from a Large Graph Using MapReduce
... a large graph, a task central to many data mining problems arising in social network analysis and ...input graph into smaller subgraphs, followed by processing different subgraphs in ...to ...
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Efficient Subgraph Query Algorithm in Large Graph
... of large graph mining. For large graphs with symmetry relation substructures, the existing decomposition-join strategy always leads to low searching ...
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Enumerating Maximal Bicliques from a Large Graph using MapReduce
... a large graph, a task central to many practical data mining problems in social network analysis and ...input graph into smaller sized subgraphs, followed by processing different subgraphs in ...to ...
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Large Graph Database for Subgraph Matching with Set Similarity Using String Metric Algorithm
... and large than now not contains important information, which may also be displayed by way of an arrangement of tokens or ...a large graph database, which retrieves subgraphs that are structurally ...
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Mining maximal cliques from a large graph using MapReduce: Tackling highly uneven subproblem sizes
... wiki-talk-3 graph the first enumeration phase takes 7 min (on 20 processors), and the sec- ond post-processing phase takes 228 min (on 80 ...dynamic graph defined by an update stream of edges, but their ...
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Large graph simplification, clustering and visualization
... Once we can differentiate nodes and edges in a network by their importance, we can sample or filter those ele- ments to simplify the network. For scale-free networks that are usually highly connected and far from planar, ...
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Cascade aware partitioning of large graph databases
... distributed graph management environment based on Pregel [20] and designed to minimize communi- cation among servers during graph query ...complementary graph partitions are computed via the ...
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Efficient Keyword Search on Large Scale Graph in a Distributed System Using Different Searching Techniques
... ABSTRACT: Graph Keyword Search has derived interest of number of research scientists, since we can represent graph models in both forms - structured and unstructured ...where graph can be much ...
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Efficient Algorithms for Querying Large-Scale Data in Relational, XML, and Graph-Structured Data Repositories
... a large number of database users) as materialized views, with the motivation that many incoming queries could be answered directly using these (concise) precomputed views, instead of costly drilling down into the ...
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Unsupervised Large Vocabulary Word Sense Disambiguation with Graph based Algorithms for Sequence Data Labeling
... Another related line of work consists of the disam- biguation algorithms based on lexical chains (Morris and Hirst, 1991), and the more recent improvements reported in (Galley and McKeown, 2003) – where threads of ...
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Fast Large Scale Approximate Graph Construction for NLP
... for large-scale noun clustering (Ravichan- dran et ...in large-scale noun clustering work, their approach had to store the ran- dom projection matrix of size D × k; where D de- notes the number of all ...
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Complexity Theory and Algorithms for Graph Problems Driven by Comparative Analysis of Large-Scale Biological Networks.
... in large-scale networks—we present two polynomial time algorithms for the densest at-least-k-subgraph problem (DalkS) when k is bounded by some constant c and propose two approximation algorithms for the densest ...
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On a sparse random graph with minimum degree three: Likely Posa s sets are large.
... are needed for G(n, m) to be connected whp, [10]. Progressively stronger ex- tensions of P´ osa’s result for G(n, m) were achieved by Korshunov[19], Koml´ os and Szemer´ edi [20], Ajtai, Koml´ os and Szemer´ edi [1], ...
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The Semifull Graph of a Graph
... other graph valued functions in graph theory were studied, for example, in [6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17,41] and also graph valued functions in domination theory were studied, for ...
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The Neighborhood Graph of a Graph
... neighborhood graph N(G) of a graph G = (V, E) is the graph with the vertex set V∪S where S is the set of all open neighborhood sets of G and with two vertices u, v ∈ V∪S adjacent if u ∈ V and v is an ...
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Map Reduce Algorithm based Fast Detection of Connected Components in Large Scale Graph Processing
... As depicted, each maper of MemoryCC loads the sub graph related with it into memory. At first this might be appeared to be hazardous because of its high memory use, however even in groups made up of product ...
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