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. ↑ 1.0 1.1 1.2 1.3 1.4 Weber, R.O.; K., Ashley; S., Brüninghaus (2005). "Textual Case-Based Reasoning". Knowledge Engineering Review 20 (3): 255–260. doi:10.1017/S0269888906000713.

## External links

* Fourth Workshop on Textual Case-Based Reasoning: Beyond Retrieval
* Textual Case-Based Reasoning Wiki

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