Computing destinations from the profile graph
Auto-Approximation of Graph Computing
... era, graph computing is one of the challenging issues because there are numerous large graph datasets emerging from real ...large graph? When it is impossible to know the exact answer ...
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Computing Lexical Chains with Graph Clustering
... Figure 2 demonstrates how an original weakly cohesive lexical chain has been divided by ChineseWhispers into five strong chains. 4 Lexical Chains for Text Summarization Lexical chains are usually evaluated in terms of ...
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Computing the Partition Function for Cliques in a Graph
... density from the graphs that have sufficiently many m-subsets of high density, even when the probability to hit such a subset at random is exponentially small in ...
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Investigations in quantum computing: causality and graph isomorphism
... grows at least as quickly as g); f (n) = Θ(g(n)) whenever both f (n) = O(g(n)) and g(n) = O(f(n)) (f and g have the same asymptotic rate of growth); and f (n) = o(g(n)) whenever f (n) = O(g(n)) but f(n) 6= Θ(g(n)) (f ...
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Computing static slices using reduced graph
... Statistics shows that almost 55% of the software’s built in these days are not useful because of their inability to meet the requirements. Hence Software testing activity is very important for launching new software in ...
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Normalized Entity Graph for Computing Local Coherence
... Table 1: Discrimination, baselines and entity graph vs. normalized entity graph 4.1 Sentence Ordering This task consists of two subtasks: discrimina- tion and insertion. In both subtasks we evaluate whether ...
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Computing Label-Constraint Reachability in Graph Databases
... db- graph in our problem is a directed graph, not a ...directed graph into a DAG by coalesc- ing the strongly connected components into a single vertex since much more path-label information is ...
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The Parameterised Complexity of Computing the Maximum Modularity of a Graph
... I Theorem 2.3. Modularity parameterised by the treewidth of the input graph G is in XP. This result makes use of standard dynamic programming techniques, and details are omitted due to space constraints. The key ...
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The parameterised complexity of computing the maximum modularity of a graph
... mum feedback vertex set for G. For background on parameterised complexity, and the complexity classes discussed here, we refer the reader to [ 5 , 11 ]. These results follow the same pattern as those obtained for the ...
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Computing GA4 Index of Some Graph Operations
... a graph means a collection of points and lines connecting a subset of ...a graph also called vertices and edges of the graph, ...connected graph is a graph such that there is a path ...
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Computing Graph Distances Parameterized by Treewidth and Diameter
... Our constructions do extend readily to directed graphs, and parameters like directed eccent- ricity, source radius, etc. can be computed within the same time bound as their undirected counterparts. We choose to claim ...
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A Random Graph Walk based Approach to Computing Semantic Relatedness Using Knowledge from Wikipedia
... for computing semantic relatedness between words or phrases to address the aforementioned ...extracted from Wikipedia and their importance in the semantic relatedness ...elements from these pages as ...
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Exploring the Computing Literature Using Temporal Graph Visualization
... evolving graph two constraints need to be ...construed from a graph is a measure of its readability. A graph that is highly readable will be easy to interpret without ...entities from ...
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Solving Hard Graph Problems with Combinatorial Computing and Optimization
... Note that (1.1) can be rewritten in matrix form as max{c T x | Ax ≤ b and x ≥ 0}, and that the minimization of f (x) can be determined by the maximization of −f (x). Linear programming has many applications in a wide ...
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A Graph Based Approach for Computing Free Word Associations
... [email protected] , [email protected] , [email protected] Abstract A graph-based algorithm is used to analyze the co-occurrences of words in the British National Corpus. It is shown that the ...
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Computing Personalized PageRank Quickly by Exploiting Graph Structures
... represented graph, we must create a new hub vertex that is connected to all these ...hub from scratch, the new hub can be efficiently composed by contracting v and all the neighboring hub ...represented ...
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Graph-shifts: Natural image labeling by dynamic hierarchical computing
... stems from the adaptive hierarchical nature of the algorithm; immediately after initialization the hierarchy represents groups of similar pixels that can get relabeled ...the graph-shifts process, we show a ...
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Computing the 4-Edge-Connected Components of a Graph in Linear Time
... (e.g., it follows from the definition of the cactus graph [1, 13]), but we provide an independent proof of this fact. Then, in Section 4.1, we show how to extend this algorithm so that it can also count the ...
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Computing Word Senses by Semantic Mirroring and Spectral Graph Partitioning
... a graph is obtained that represents words and their translations from a paral- lel corpus or a bilingual ...the graph holds information about the different meanings of words that occur in the ...
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Beehive: A Framework for Graph Data Analytics on Cloud Computing Platforms
... The unit of data relocation is all the data related to a vertex. A. Distributed Data Store Beehive framework provides the abstraction of a shared storage implemented as a distributed key-value based object store. The ...
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