English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Zendy Plus

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Zendy Tools

Zendy Open

The graph-navigability problem concerns how one can find as short paths aspossible between a pair of vertices, given an incomplete picture of a graph. Westudy the navigability of graphs where the vertices are tagged by a number(between 1 and the total number of vertices) in a way to aid navigation. Thisinformation is too little to ensure errorfree navigation but enough, as we willshow, for the agents to do significantly better than a random walk. In oursetup, given a graph, we first assign information to the vertices that agentscan utilize for their navigation. To evaluate the navigation, we calculate theaverage distance traveled over random pairs of source and target and differentgraph realizations. We show that this type of embedding can be made quiteefficiently; the more information is embedded, the more efficient it gets. Wealso investigate the embedded navigational information in a standard graphlayout algorithm and find that although this information does not makealgorithms as efficient as the above-mentioned schemes, it is significantlyhelpful.

Pathlength scaling in graphs with incomplete navigational information