Jump to content

Textual case-based reasoning

From Wikipedia, the free encyclopedia
The printable version is no longer supported and may have rendering errors. Please update your browser bookmarks and please use the default browser print function instead.

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. ^ a b c d e Weber, R.O.; K., Ashley; S., Brüninghaus (2005). "Textual Case-Based Reasoning". Knowledge Engineering Review. 20 (3): 255–260. CiteSeerX 10.1.1.91.9022. doi:10.1017/S0269888906000713. S2CID 11502038.