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

We introduce two algorithms, RECURSIA and RRT, designed to increase thecompression factor achievable using point-set cover algorithms based on the SIAand SIATEC pattern discovery algorithms. SIA computes the maximal translatablepatterns (MTPs) in a point set, while SIATEC computes the translationalequivalence class (TEC) of every MTP in a point set, where the TEC of an MTP isthe set of translationally invariant occurrences of that MTP in the point set.In its output, SIATEC encodes each MTP TEC as a pair, <P,V>, where P is thefirst occurrence of the MTP and V is the set of non-zero vectors that map Ponto its other occurrences. RECURSIA recursively applies a TEC cover algorithmto the pattern P, in each TEC, <P,V>, that it discovers. RRT attempts to removetranslators from V in each TEC without reducing the total set of points coveredby the TEC. When evaluated with COSIATEC, SIATECCompress and Forth's algorithmon the JKU Patterns Development Database, using RECURSIA with or without RRTincreased compression factor and recall but reduced precision. Using RRT aloneincreased compression factor and reduced recall and precision, but had asmaller effect than RECURSIA.

RecurSIA-RRT: Recursive translatable point-set pattern discovery with removal of redundant translators