Vector Space Model
Stanford UniversitySemantic embeddingSentiment classification
Vector Space Model is a semantic embedding model from Stanford University released in 2011 with 255000.0 parameters.
About Vector Space Model
Unsupervised vector-based approaches to semantics can model rich lexical meanings, but they largely fail to capture sentiment information that is central to many word meanings and important for a wide range of NLP tasks. We present a model that uses
Details
- Provider
- Stanford University
- Task
- Semantic embedding,Sentiment classification
- Parameters
- 255000.0
- Released
- 2011-06-19