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 Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

The use of lexical semantic knowledge in information retrieval has been a field of active study for a long time. Collaborative knowledge bases like Wikipedia and Wiktionary, which have been applied in computational methods only recently, offer new possibilities to enhance information retrieval. In order to find the most beneficial way to employ these resources, we analyze the lexical semantic relations that hold among query and document terms and compare how these relations are represented by a measure for semantic relatedness. We explore the potential of different indicators of document relevance that are based on semantic relatedness and compare the characteristics and performance of the knowledge bases Wikipedia, Wiktionary and WordNet.

A study on the semantic relatedness of query and document terms in information retrieval