Sentence examples for effective graphs from inspiring English sources

Designing effective graphs and knowing how to interpret them is critical.

Poor structure ruins otherwise effective graphs by accidentally distorting the data, making them hard to read, or distracting the readers if purposefully misleading (Doumont 2009).

This paper presents two novel, highly effective graph clustering-based discretization algorithms that are graph clustering-based discretization of splitting method (GraphS) and merging method (GraphM).

Three spectral graph metrics are considered: spectral radius, effective graph resistance and algebraic connectivity.

It draws upon the literatures concerning memory, impression management and effective graph design.

Specifically, we construct a simple but effective graph to search the local relationship of data points.

We propose an effective graph partitioning technique that achieves low replication factor and good load balance factor.

The intuition allows more refined data-wise relations to be obtained and used with the effective graph clustering technique based on normalized association to discover nature graphs accurately.

We propose an effective graph partitioning technique that achieves low communication cost and good load balance among computers at the same time.

Graph-theoretic characterizations of the optimal subset design are obtained: in particular, the design is connected to the structure of a reduced effective graph defined from the essentially-nonnegative matrix.

The fourth paper of this issue: Graph Partitioning for Distributed Graph Processing by Makoto Onizuka, Toshimasa Fujimori, and Hiroaki Shiokawa, presents effective graph partitioning techniques to achieve low communication cost and good load balance among computational nodes at the same time in a distributed system.