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

Vocabulary learning by children can be characterized by many biases. Whenencountering a new word, children as well as adults, are biased towardsassuming that it means something totally different from the words that theyalready know. To the best of our knowledge, the 1st mathematical proof of theoptimality of this bias is presented here. First, it is shown that this bias isa particular case of the maximization of mutual information between words andmeanings. Second, the optimality is proven within a more general informationtheoretic framework where mutual information maximization competes with otherinformation theoretic principles. The bias is a prediction from moderninformation theory. The relationship between information theoretic principlesand the principles of contrast and mutual exclusivity is also shown.

The optimality of attaching unlinked labels to unlinked meanings