Sentence examples for big graph from inspiring English sources

Clustering phenomenon is very common in big graph data.

Our design can efficiently achieve a tradeoff between data authenticity (when publishing dynamically growing big graph data) and data privacy (when disseminating big graph data).

These schemes are the bases and prerequisites for big graph partitioning.

Using a single commodity computational node to partition big graph is very difficult.

To improve the performance on big graph data, we also propose a multi-stage strategy.

It finds clusters from a big graph data by only locally exploring the graph.

The internet has bestowed cult status on wonkish members of Congress who bring big graphs and charts to debates.

Local computations are good for big graphs.

In general, big graphs are normally heterogeneous.

Querying big graphs is hard, and cleaning big graphs is even harder.

We approach this by making big graphs small.