Tagged “lexical”
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What keyword search misses
Vocabulary mismatch: when the user's words and the document's words don't overlap, term scoring has nothing to score. Where stemming stops helping.
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Query expansion, and how it drifts
Adding terms to a query fixes vocabulary mismatch and dilutes precision at the same time. Where synonyms belong, and how expansion goes wrong.
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Learned sparse retrieval, the third signal
A model that predicts term weights and adds terms the document never contained. What it inherits from lexical search, and what it costs.
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Typos, and which retriever forgives them
A misspelling deletes a lexical match and blurs a dense one. Fuzzy matching, correction, and why the fix depends on which word was misspelled.
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Which field the match landed in
A title match and a body match are not worth the same. Field weighting, why concatenating fields loses information, and how boosts go wrong.
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The analyser decides what you can match
Tokenisation, stemming and stop words run before scoring. Get them wrong and lexical retrieval cannot find terms that are plainly in the text.
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When the query and the document aren't in the same language
Term matching across languages scores zero. Multilingual embeddings, translating the query, and why a mixed-language corpus fails per language.
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Making a term mandatory
Term scoring is additive, so a document missing the decisive word can still win. How required terms work, and what they do to a hybrid pipeline.