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/

Global: Zendy Plus annual

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

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Knowledge graphs (KGs) provide information in machine interpretable form. Incases where multiple KGs are used in the same system, that information needs tobe integrated. This is usually done by automated matching systems. Most ofthose systems consider only 1:1 (binary) matching tasks. Thus, matching alarger number of knowledge graphs with such systems would lead to quadraticefforts. In this paper, we empirically analyze different approaches to reducethe task of multi-source matching to a linear number of executions of binarymatching systems. We show that the matching order of KGs and the multi-sourcestrategy actually matter and that near-optimal results can be achieved withlinear efforts.

Order Matters: Matching Multiple Knowledge Graphs