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

Analytical queries often require a mixture of relational and linear algebraoperations applied to the same data. This poses a challenge to analytic systemsthat must bridge the gap between relations and matrices. Previous work hasmainly strived to fix the problem at the implementation level. This paperproposes a principled solution at the logical level. We introduce therelational matrix algebra (RMA), which seamlessly integrates linear algebraoperations into the relational model and eliminates the dichotomy betweenmatrices and relations. RMA is closed: All our relational matrix operations areperformed on relations and result in relations; no additional data structure isrequired. Our implementation in MonetDB shows the feasibility of our approach,and empirical evaluations suggest that in-database analytics performs well formixed workloads.

A Relational Matrix Algebra and its Implementation in a Column Store