Textual case-based reasoning

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
  1. Weber, R.O.; K., Ashley; S., Brüninghaus (2005). "Textual Case-Based Reasoning". Knowledge Engineering Review. 20: 255–260. Retrieved 14 July 2021.{{cite journal}}: CS1 maint: url-status (link)
This article is issued from Wikipedia. The text is licensed under Creative Commons - Attribution - Sharealike. Additional terms may apply for the media files.