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

The current mode of biomedical literature search is severely limited ineffectively finding information relevant to specialists. A potential approachto solving this problem is exploratory search, which allows users tointeractively navigate through a vast document collection. As the first steptoward exploratory search for specialists in biomedicine, this paper develops amethodology to evaluate quality of document clusters. For this purpose, weincorporate human expertise into data set creation and evaluation framework byleveraging MeSH terms as semantic anchors. In addition, we investigate thebenefit of full-text data for improving cluster quality.

Toward Exploratory Search in Biomedicine: Evaluating Document Clusters by MeSH as a Semantic Anchor