Keyword Matching
A technical logic that extracts keywords such as key skills, tool names and industry terminology from a target job description, compares them with resume text to compute coverage, and flags missing items.
Timeline (last 90 days)
Traditional ad systems rely on keyword matching and user profile tags; when facing conversations that span several turns and whose context evolves, keyword methods become almost ineffective.
Keyword matching splits a query into terms and relies on inverted indexes and statistical signals such as TF-IDF or BM25 to judge relevance; semantic matching encodes the entire context into a dense vector and measures semantic closeness with cosine similarity.
Traditional automation solutions usually rely on rule engines or simple keyword matching and struggle to understand context and semantic relationships; for example, they cannot distinguish the semantic difference between "temperature slightly above the setpoint but lasting very briefly" and "temperature persistently exceeding the limit".
Keyword matching easily leads to excessive piling up of jargon; in practical use it still needs to be combined with semantic understanding and human judgment to keep the resume readable.
Claude Code's keyword-matching recall mechanism means that if the original discussion was about "Stripe" and the later question is about "payment processing," the system very likely will not find that conversation.
Traditional patent searching mainly relies on keyword matching, meaning the system returns documents that contain the query terms.
All Facts (6)
Traditional ad systems rely on keyword matching and user profile tags; when facing conversations that span several turns and whose context evolves, keyword methods become almost ineffective.
50%UnverifiedKeyword matching splits a query into terms and relies on inverted indexes and statistical signals such as TF-IDF or BM25 to judge relevance; semantic matching encodes the entire context into a dense vector and measures semantic closeness with cosine similarity.
50%UnverifiedTraditional automation solutions usually rely on rule engines or simple keyword matching and struggle to understand context and semantic relationships; for example, they cannot distinguish the semantic difference between "temperature slightly above the setpoint but lasting very briefly" and "temperature persistently exceeding the limit".
50%UnverifiedKeyword matching easily leads to excessive piling up of jargon; in practical use it still needs to be combined with semantic understanding and human judgment to keep the resume readable.
50%UnverifiedClaude Code's keyword-matching recall mechanism means that if the original discussion was about "Stripe" and the later question is about "payment processing," the system very likely will not find that conversation.
50%UnverifiedTraditional patent searching mainly relies on keyword matching, meaning the system returns documents that contain the query terms.
50%