Ontology based expert systems – replication of human learning

  • Rahul Matkar
  • Ajit Parab


This paper mainly focuses of the learning ability of the Expert Systems. This paper presents an elite system well known as Expert Systems, which tries to replicate the behavior of a ‛Human Expert’. The expert systems work on the concept of ‛Knowledge Base’. This knowledge base is developed by a ‛Knowledge Engineer’ after conducting a series of interviews with the ‛Human Expert’. The ‛Inference Engine’ uses the facts from the ‛Knowledge Base’ in order to derive a solution to a problem. The performance of the Expert System fully depends on the quality of the Knowledge Base and the Inference Engine.The major issue to be considered under the development of theExpert systems is the ability to learn things by themselves. Expert Systems ‛Replicate’ the approach of human experts towards solving a problem, similarly the expert systems can also ‛Replicate the behavior of Human Learning’. While learning a new fact humans use their existing knowledge and try to respond to the new fact accordingly. Similarly, an Expert System, if given a ‛Baseline – A strict set Rules to follow’ and the ‛Ability to Derive a Relation between various Facts (An Ontology)’ while learning, they can also ‛derive’ or ‛learn’ new facts the same way Human Experts learn or Expand their knowledge.


Knowledge Base Expert System Human Expert Human Learning Inference Engine 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer India Pvt. Ltd 2011

Authors and Affiliations

  • Rahul Matkar
    • 1
  • Ajit Parab
    • 2
  1. 1.Vidyalankar School of Information TechnologyMumbaiIndia
  2. 2.Computer Technology DepartmentBabasaheb Gawde Institute of TechnologyMumbaiIndia

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