The Future has Arrived for Data-Driven Expert System Software

Background

Expert systems have traditionally been developed with most of the knowledge buried in the program logic. Programmers were needed to maintain the expert rules. This approach made developing the rules slow, expensive and error prone. The key to a successful expert system is a flexible database that allows the experts to maintain the rules directly. The expert logic must be encapsulated in the database and not in the program logic. The interface used to transfer the knowledge from the expert to the database must be robust, easy to use, flexible and allow for easy validation..

Can Logic Be Fuzzy?

"Fuzzy Logic" is a term dealing with approximate reasoning rather than precise reasoning. Our data-driven expert system analyzes situations. Situations are described by the characteristics that describe the system both in a positive and negative manner. Expert should be able to model the situations that they are dealing with to see how the knowledgebase deals with it.

This does not say that an expert system always yields an exact outcome. The knowledge stored in an expert system has limits. The limits are in the scope of the system and the depth of it's knowledge. Building an knowledge base is not a project with a fixed completion point. It's a ongoing process, The information and knowledge that we continually acquire needs to fed to the expert system. However, since the knowledge is in the database not the program code, the program that maintains the database can be completed.

Expert Logic vs. Sequential Logic

Programming logic has traditionally been sequential. The logic flows sequentially and branches based on predefined conditions. Expert logic is situational. Every situation is different. The program needs to respond to the information that is being gathered from the user. The basic logic flow in an expert system is:

  1. Capture information
  2. Evaluate the information
    • Draw a conclusion.
    • Request more information
    • Act on the information
  3. Additionally, the user may be able to query the system to determine the possible solutions and outcomes in the midst of a situation. This is useful for the expert when they are developing the rules and for the user when the expert system has reached the limits of it's knowledge. 
What Can an Data-Driven Expert System Do?

Data-Driven Expert System excel at investigative work. An investigative system gathers data. The data is analyzed to determine what additional data needs to be gathered to complete the investigation and draw the proper conclusion. 

Typical acts performed by the expert system depend on the application: 

  1. Investigative or Audit
    • Send an e-mail, letter or fax
    • Initiate a phone call
    • Request a credit report or other background document
    • Initiate a transaction with another system. 
    • Determine whether the case is satisfactory or defective
    • Score an application.
    • Help to uncover fraud.
    • Reveal practices contrary to regulatory or corporate guidelines.
  1. Medical
    • Diagnosis
    • Recommend dosage levels
    • Determine admission status
    • Profile risk

  2. Consumer Goods and Services

    • Troubleshooting
    • Automated support
    • Determine admission status
    • Profile risk
    • Telemarketing
Benefits of a Data-Driven Expert System
  1. Reduced training requirements. The computer is trained to do the expert analysis. Less skilled people can operate the system and interpret the results.
  2. Consistent Analysis.
  3. Overall effectiveness.
  4. Tailored responses to individual situations.
  5. A readily available source of information.
  6. Speed of Analysis.
Keys to a Successful Data-Driven Expert System
  1. Fast. Situations must be analyzed as fast as the user can enter information.
  2. Easy. Entry must be easy. Voice recognition systems will be a key factor in many applications.
  3. Powerful User Interface for Rules input and analysis.
  4. Ability to handle large amounts of data 
  5. Easy access to reference materials.
  6. Statistical analysis capabilities.
Example Expert System Data Gathering Screen

This screen illustrates one way to capture information. The user categorizes information into sections. Some sections can occur once in the case, others multiple. Each section can be completed independently. The Questions for each section are shown on the lest with their answer. The highlighted question has additional information and reference material available on the bottom. The bottom along the right allow the user to perform special functions like collect special information, or manage the actions created for the situation.

Example Expert System Data Gathering Screen

The screen used for mortagage auditing by many leading lenders.

Construction of the Rules Database

The internal design of the rules database has many components

  1. Questions of many different types need to asked. The various formats need to be handled.
  2. The possible answers value that have an affect recording.
  3. The facts need to be grouped into conditions. When a condition is met, several things could happen.
  1. A series of questions could be asked or actions staged for execution.
  2. A condition could prevent an action or question from being asked.
  3. A conclusion could be reached. It could need further support and documentation for reporting.

Mitten Software Can Help Develop Your Expert System.

Contact 952-745-4941, ask for Jim.    Or send an e-mail to answers@mittensoftware.com

 

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