Distributional Semantic Modeling Algorithm
(Redirected from distributional semantic models (DSMs))
A Distributional Semantic Modeling Algorithm is a lexical semantic modeling algorithm that makes use of a distributional lexical semantics heuristic.
- AKA: Distributional Text-Item Model Training Algorithm.
- Context:
- It can be applied by a Distributional Semantic Modeling System (solve a Distributional Semantic Modeling Task).
- It can make use of a Word-Word Co-occurrence Matrix.
- It can range from being a Count-based Distributional Semantic Modeling Algorithm to being a Prediction-based Distributional Semantic Modeling Algorithm.
- It can range from (typically) being a Distributional Word Model Training Algorithm to being a Distributional Phrase Model Training Algorithm to being a Distributional Sentence Model Training Algorithm to being a Distributional Document Model Training Algorithm.
- …
- Counter-Example(s):
- See: Distributional Text-Item Model, Distributional Word Vectorizing Function.
References
2010
- Magnus Sahlgren. https://www.sics.se/~mange/research.html
- QUOTE: My research is focused on how semantic knowledge is acquired and represented in man and machine. In particular, I study the distributional approach to semantic knowledge acquisition, in which semantic information is extracted from cooccurrence statistics. The underlying idea is that meanings are correlated with the distributional patterns of linguistic entities.