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[]

^ ^a ^b ^c ^d ^e Weber, R.O.; K., Ashley; S., Brüninghaus (2005). "Textual Case-Based Reasoning". Knowledge Engineering Review. 20: 255–260. Retrieved 14 July 2021.

External links[]

This artificial intelligence-related article is a stub. You can help Wikipedia by .

[:0-1] Weber, R.O.; K., Ashley; S., Brüninghaus (2005). "Textual Case-Based Reasoning". Knowledge Engineering Review. 20: 255–260. Retrieved 14 July 2021.

[1]