Name
Abstract | ||
|---|---|---|
Although crowdsourcing has been proven efficient as a mechanism to solve independent tasks for on-line production, it is still unclear how to define and manage workflows in complex tasks that require the participation and coordination of different workers. Despite the existence of different frameworks to define workflows, we still lack a commonly accepted solution that is able to describe the most common workflows in current and future platforms. In this paper, we propose CrowdWON, a new graphical framework to describe and monitor crowd processes, the proposed language is able to represent the workflow of most well-known existing applications, extend previous modelling frameworks, and assist in the future generation of crowdsourcing platforms. Beyond previous proposals, CrowdWON allows for the formal definition of adaptative workflows, that depend on the skills of the crowd workers and/or process deadlines. CrowdWON also allows expressing constraints on workers based on previous individual contributions. Finally, we show how our proposal can be used to describe well known crowdsourcing workflows. |
Year | Venue | Keywords |
|---|---|---|
2015 | PROCEEDINGS OF THE TWENTY-NINTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE | process,crowdsourcing |
Field | DocType | Citations |
Data science,Crowdsourcing,Computer science,Knowledge management,Formal description,Artificial intelligence,Workflow nets,Workflow,Machine learning | Conference | 0 |
PageRank | References | Authors |
0.34 | 8 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| David Sanchez-Charles | 1 | 4 | 1.41 |
| Victor Muntés-Mulero | 2 | 204 | 22.79 |
| Marc Sole | 3 | 16 | 1.68 |
| Jordi Nin | 4 | 311 | 26.53 |