Abstract
Creating incentives for knowledge workers to share their knowledge within an organization continues to be a challenging task. Strong, innate behaviors of the knowledge worker, such as self-preservation and self- advancement, are difficult to overcome, regardless of the level of knowledge. Many incentive policies simply focus on providing external pressure to promote knowledge sharing. This work describes a technical approach to motivate sharing. Utilizing text analysis and machine learning techniques to create an enhanced knowledge sharing experience, a prototype system was developed and tested at Oak Ridge National Laboratory that reduces the overhead cost of sharing while providing a quick, positive payoff for the knowledge worker. This work describes the implementation and experiences of using the prototype in a corporate production environment.
