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

In this paper we generalize the definition of "Search Trees" (ST) to enablereference values other than the key of prior inserted nodes. The idea builds onthe assumption an $n$-node AVL (or Red-Black) requires to assure $O(\log_2n)$worst-case search time, namely, a single comparison between two keys takesconstant time. This means the size of each key in bits is fixed to $B=c\log_2n$ ($c\geq1$) once $n$ is determined, otherwise the $O(1)$-time comparisonassumption does not hold. Based on this we calculate \emph{ideal} referencevalues from the mid-point of the interval $0..2^B$. This idea follows`recursively' to assure each node along the search path is provided a referencevalue that guarantees an overall logarithmic time. Because the search treeproperty works only when keys are compared to reference values and these valuesare calculated only during searches, we term the data structure as the HiddenBinary Search Tree (HBST). We show elementary functions to maintain the HSBTheight $O(B)=O(\log_2n)$. This result requires no special order on the input --as does BST -- nor self-balancing procedures, as do AVL and Red-Black.

The Hidden Binary Search Tree:A Balanced Rotation-Free Search Tree in the AVL RAM Model