New Applications … New Competitive Advantages

A great advantage Bayesian network technology has over other technologies is its capacity for incorporating into solutions historical information (what's happened in the past), physicial information (weights and measures), logical rules (if-then-else) and, most importantly, expert knowledge. By combining these information sources into Bayesian network models, applications can begin to uncover hidden information, as well as answer questions that were heretofore unanswerable. Following are some examples.

Résumé Assessment System
IET developed a prototype system that automatically assesses the truthfulness of résumé information using open source data. The prototype assesses whether educational credentials, job timelines and jobs held make sense and reports on their credibility. The prototype can be extended to include whether a job candidate is a "good fit" for a job, an organization or even a customer.

Distance learning or e-learning holds great promise for wide access, lower costs and just-in-time learning. However, adoption of e-learning has been slowed by high dropout rates and a one-size-fits-all mentality. IET developed a prototype system that automatically assembles e-learning course content according to the learner’s objective, the learner’s current competencies and the course material at hand. The system is also capable of on-the-fly adaptation to a learners progress or lack thereof.