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It corresponds to the best graph organization regarding the purity measure.
Conventionally, graph organization is built on top of the relational (a.k.a., SQL) storage and graphs are stored as triplets [6, 22].
As described in the next section, by exploiting a graph organization for CH information, the dissemination model provides savvy users with an open interface for storytelling, resulting in more freedom for creativity and enhancing interactivity in the presentations of narratives.
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But a last-minute tip coming in suggests that Facebook will also be altering the social graph, making organization easier.
This measure is a structural approach, which explores the directed acyclic graph (DAG) organization of ChEBI [22].
Therefore, we also assume such graph-specific data organization.
Using cell-graphs, the structural organization of tissue samples are captured.
Using resting-state functional magnetic resonance imaging and graph analysis, the topological organization of the functional brain network connectivity was explored in patients with left-sided onset semantic variant (SV) of primary progressive aphasia relative to healthy controls.
Bearing this in mind, a suggestive idea is to obtain a graph with the best organization of components without using a unique value of K, i.e., each component has its own optimal value of K, denoted as K α for component C α. Therefore, the rationale for obtaining the optimal graph is to construct K=1,…,Kmax associated graphs while keeping the best components found at each K throughout this process.
However, many network measures were designed to be calculated on binary graphs, whereas functional brain organization is typically inferred from a continuous measure of correlations in temporal signal between brain regions.
We show that geometric random graphs capture the network organization of RIGs better for larger than for smaller proteins.
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