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 Tools annual

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 Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

Efficiently finding doctors and locations is an important search problem forpatients in the healthcare domain, for which traditional information retrievalmethods tend not to work optimally. In the last ten years, knowledge graphs(KGs) have emerged as a powerful way to combine the benefits of gleaninginsights from semi-structured data using semantic modeling, natural languageprocessing techniques like information extraction, and robust querying usingstructured query languages like SPARQL and Cypher. In this short paper, wepresent a KG-based search engine architecture for robustly finding doctors andlocations in the healthcare domain. Early results demonstrate that our approachcan lead to significantly higher coverage for complex queries without degradingquality.

A Knowledge Graph-Based Search Engine for Robustly Finding Doctors and Locations in the Healthcare Domain