Textual case-based reasoning

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Textual case-based reasoning (TCBR) is a subtopic of case-based reasoning, in short CBR, a popular area in artificial intelligence. CBR suggests the ways to use past experiences to solve future similar problems, requiring that past experiences be structured in a form similar to attribute-value pairs. This leads to the investigation of textual descriptions for knowledge exploration whose output will be, in turn, used to solve similar problems.[1]

Subareas

Textual case-base reasoning research has focused on:

  • measuring similarity between textual cases[1]
  • mapping texts into structured case representations[1]
  • adapting textual cases for reuse[1]
  • automatically generating representations.[1]

References

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