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Knowledge Acquisition Concept in Artificial Intelligence



  • Knowledge Acquisition is the transformation of knowledge from the forms in which it exists into forms that can be used in a knowledge based system
  • The primary goal discover, develop and implement efficient, effective method of knowledge acquisition
  • It is a process of adding new knowledge to a knowledge base refining, improving previously acquire knowledge
  • Acquisition is usually associated with some definite purpose such as expanding the capabilities of system, improving or enhancing the performance of some specific tasks
  • Acquired knowledge consist of facts, rules, concept, procedure, formulas, relationship, stats, plans,heuristic or any relevant information
  • The sources can be anyone of the following like-that , report, electronic document,database,newspaper,news channel,soft copy of document etc
Three model of knowledge acquisition -
  1. Handcrafting - means code knowledge is converted into program directly
  2. Knowledge Engineering - means working with expert system to organise knowledge in a suitable form for an expert system to use.
  3. Machine Learning - means to extract the knowledge from training examples
Challenges/ Issues in knowledge Acquisition
  1. most knowledge is in the heads of experts
  2. experts have vast amount of knowledge
  3. experts are very busy and valuable people
  4. each expert doesn't know everything
  5. knowledge is short lived
  6. difference in expert opinions
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