LatentSemanticMapping provides latent semantic analysis on macOS for classifying and categorizing text by meaning. You build a map with LSMMap that learns the associations between categories and their characteristic text, then evaluate new content represented as LSMText against it. The framework returns the best-matching categories through LSMResult, letting you sort or label text according to the meaning it most closely reflects.
Semantic Maps 1
The trainable map that learns associations between categories and their characteristic text.
- ClLSMMap@typedef LSMMapRef
Text Representation 1
The container for the text you add for training or evaluate for categorization.
- ClLSMText@typedef LSMTextRef
Evaluation Results 1
The outcome of evaluating text against a map, ranking the best-matching categories.
- ClLSMResult@typedef LSMResult
Type Aliases 1
- TyLSMCategory@typedef LSMCategory