Sentence Embedding

Sentence Embedding is a key technology in natural language processing, aimed at converting sentences into fixed-length vector representations to capture their semantic information. Through deep learning models, Sentence Embedding can achieve efficient encoding of sentence structure and context, thereby supporting more accurate semantic understanding and matching. This technology is widely applied in areas such as information retrieval, sentiment analysis, and machine translation, significantly enhancing the performance and robustness of natural language processing systems.