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

The success of software crowdsourcing depends on active and trustworthy poolof worker supply. The uncertainty of crowd workers' behaviors makes itchallenging to predict workers' success and plan accordingly. In a competitivecrowdsourcing marketplace, competition for success over shared tasks addsanother layer of uncertainty in crowd workers' decision-making process.Preliminary analysis on software worker behaviors reveals an alarming taskdropping rate of 82.9%. These factors lead to the need for an automatedrecommendation system for CSD workers to improve the visibility andpredictability of their success in the competition. To that end, this paperproposes a collaborative recommendation system for crowd workers. The proposedrecommendation system method uses five input metrics based on workers'collaboration history in the pool, workers' preferences in taking tasks interms of monetary prize and duration, workers' specialty, and workers'proficiency. The proposed method then recommends the most suitable tasks for aworker to compete on based on workers' probability of success in the task.Experimental results on 260 active crowd workers demonstrate that justfollowing the top three success probabilities of task recommendations, workerscan achieve success up to 86%

From Zero to The Hero: A Collaborative Market Aware Recommendation System for Crowd Workers