Sentence Embedding Model
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A Sentence Embedding Model is a text-item embedding model for sentences that can be referenced by a sentence embedding encoder.
- AKA: Sentence Encoding Model.
- Context:
- It can (often) be based on neural network architectures
- It can (often) be trained on a Large Corpus of Text.
- It can utilize techniques such as Word Embedding Aggregation, Sequence Modeling, and Attention Mechanisms.
- It can range from being a Pure Sentence Embedding Model to being a Contextually-Informed Sentence Embedding Model.
- It can range form being a Domain-Specific Sentence Embedding Model to being a Universal Sentence Embedding Model.
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- Example(s):
- Counter-Example(s):
- A Word Embedding Model, which focuses on generating embeddings for individual words rather than whole sentences.
- A Document Embedding Model, which is designed to generate embeddings for entire documents, which may contain multiple sentences or paragraphs.
- See: Vector Space Model, Semantic Analysis, Word Embedding, Document Embedding.