Abstract
We propose CMSMs, a novel type of generic compositional models for syntactic and semantic aspects of natural language, based on matrix multiplication. We argue for the structural and cognitive plausibility of this model and show that it is able to cover and combine various common compositional NLP approaches ranging from statistical word space models to symbolic grammar formalisms.
Keywords
Computer scienceRotation formalisms in three dimensionsNatural language processingArtificial intelligenceGrammarPrinciple of compositionalityNatural languageSpace (punctuation)Cover (algebra)Word (group theory)LinguisticsMathematics
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Publication Info
- Year
- 2010
- Type
- article
- Pages
- 907-916
- Citations
- 53
- Access
- Closed
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Cite This
Sebastian Rudolph,
Eugenie Giesbrecht
(2010).
Compositional Matrix-Space Models of Language.
, 907-916.