Getting started on knowledge engineering | Problems and responses

Expert systems can respond to real world problems. It’s important for knowledge engineers to decide on the right problem before work begins.

Defining the problem and the response

Earlier, we talked about 3 key questions a knowledge engineer should consider:

  1. Is this a problem for non-experts that wouldn’t be a problem for experts?
  2. Is there a relatively uniform knowledge domain here?
  3. Would expert reasoning or guidance help non-expert users with the problem?

A next step is defining the problem and a proposed response. The problem definition will help knowledge engineers understand what they are working to solve and who it’s affecting. The response refers to the proposed outcomes for users.

The problem definition & response can serve as vision statement to communicate the objectives of the knowledge engineering work. It also keeps the work on track. Because knowledge engineering can take a long time, people might forget what they set out to do in the first place.

It’s easy to get bogged down on very small, but very difficult issues in knowledge engineering. A clear focus on the problem you meant to solve and the response you intended to provide can serve as a reflection point and problem solving tool if this happens. And it will happen.

Elements of a problem definition & response can include:

1. A one sentence description of the problem, identifying the people who are suffering as because of it:

Problem: People with fitness club membership contract disputes aren’t aware of the special rights they have under consumer laws and regulations.

2. A one sentence description of the positive impact or outcome that will be provided through the expert system:

Response: The expert system will diagnose fitness club membership contract disputes, provide information and guidance to consumers, and empower them to exercise their specific legal rights to achieve better outcomes.

Response & Outcome types

Expert systems can provide several types of responses, including any combination of the following:

  • Diagnosing different types of problems to various degrees of specificity or granularity
  • Providing specific information about a diagnosed problem
  • Providing self-help tools and steps to address the problem
  • Guidance about a user’s options for dealing with the problem and how to access them

Problems that can be addressed by these types of responses will make good candidates for expert systems. Remember: expert systems can’t pick up your dry cleaning or provide answers beyond the grasp of human experts.


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