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]
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External links[]
Categories:
- Artificial intelligence stubs
- Classification algorithms
- Inductive reasoning
- Natural language processing