The stem-based vector space model for automatic resource allocation in workflow

In the context of workflow, resource allocation is often performed manually and empirically. In this paper, we present a novel approach based on stem-based vector space model (VSM) to automate the resource allocation works. The VSM similarity is utilized to compute the cohesion measures between the resources and the tasks, and the cohesion measures are then used to rank the resource candidates, and the resource with the highest score will be allocated to the specific workflow task. The initial evaluation on our experiments shows that our method can efficiently predicate the performers for the workflow tasks with good precision.