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

Modern photometric multiband digital surveys produce large amounts of datathat, in order to be effectively exploited, need automatic tools capable toextract from photometric data an objective classification. We present here anew method for classifying objects in large multi-parametric photometric databases, consisting of a combination of a clustering algorithm and a clusteragglomeration tool. The generalization capabilities and the potentialities ofthis approach are tested against the complexity of the Sloan Digital Sky Surveyarchive, for which an example of application is reported.

Steps toward a classifier for the Virtual Observatory. I. Classifying the SDSS photometric archive