Unverified50% confidenceFactExact time
Keyword retrieval tokenizes the query, counts the number of matched terms in each chunk, and scores and ranks them proportionally; it is simple to implement, costs nothing extra, and produces interpretable results, but can only match literal overlaps.
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50%
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Long-term
Relevance
10/13/2026
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Verified关键词搜索基于精确字符匹配无法理解同义词,语义搜索依赖向量嵌入可捕捉语义关联,两者结合的混合检索效果优于单一方法74% similarVerifiedIn the knowledge retrieval stage, the user's question is converted into a query vector via an embedding model, similarity is computed against the text chunk vectors in the knowledge base (typically using cosine similarity), and the top-K segments are returned by ranking.72% similarUnverified掌握搜索词数据后,创作者能更有针对性地优化内容标题、简介和标签,从而提升在搜索结果中的可见度70% similarUnverifiedTraditional search engines perform keyword matching based on inverted indexes and statistical methods such as TF-IDF, making it difficult to establish effective document relevance rankings when queries are too short or too vague.70% similarUnverified倒排索引是搜索引擎核心数据结构,建立从词到文档的映射关系,使关键词检索时间复杂度接近O(1)69% similar
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