Unverified60% confidenceSolutionExact time
Synonym normalization can be achieved by using sentence embedding models such as Sentence-BERT to map words into dense vectors, and then computing semantic proximity via cosine similarity.
2
Sources
60%
Confidence
Long-term
Relevance
7/14/2026
First Seen
Sources
语音驱动几何交互：LLM语义解析与Function Calling架构实践
Related Claims
UnverifiedThe role of an embedding model is to convert text into high-dimensional vectors, enabling machines to measure semantic similarity in a mathematical way.79% similarVerifiedSemantic retrieval is based on mathematical metrics such as cosine similarity rather than simple keyword matching.79% similarUnverifiedSentence-BERT通过孪生网络结构将句子映射为固定维度的稠密向量，专为句子级语义相似度优化78% similarUnverifiedSemantic chunking uses embedding models to assess semantic similarity between adjacent sentences and splits at semantic breaks, but still cannot guarantee logical coherence across paragraphs.77% similar
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