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

Labeled datasets are essential for supervised machine learning. Various datalabeling tools have been built to collect labels in different usage scenarios.However, developing labeling tools is time-consuming, costly, andexpertise-demanding on software development. In this paper, we propose aconceptual framework for data labeling and OneLabeler based on the conceptualframework to support easy building of labeling tools for diverse usagescenarios. The framework consists of common modules and states in labelingtools summarized through coding of existing tools. OneLabeler supportsconfiguration and composition of common software modules through visualprogramming to build data labeling tools. A module can be a human, machine, ormixed computation procedure in data labeling. We demonstrate the expressivenessand utility of the system through ten example labeling tools built withOneLabeler. A user study with developers provides evidence that OneLabelersupports efficient building of diverse data labeling tools.

OneLabeler: A Flexible System for Building Data Labeling Tools