Practice query understanding vocabulary: query parsing, expansion, spell correction, intent classification, and query normalization in search engineering.
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'Query _____ (synonyms, stemming)' adds related terms to improve search recall.
Query expansion adds synonyms, related terms, and stemmed variants to the user's query to retrieve more relevant results the user might not have found with exact keyword matching.
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'The user typed java script — normalize to javascript.' What query processing step is this?
Query normalization standardizes query tokens (merging 'java script' to 'javascript', lowercasing, removing special characters) to improve matching against the index.
The three main query intent classes are: navigational (find a specific site), informational (learn about a topic), and transactional (complete an action like buying). Each warrants different ranking strategies.
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'Spell correction' in search is important because:
Spell correction (e.g., 'serach' → 'search') is critical for search precision — typos are common and without correction they result in zero results for valid user intents.
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What is 'query parsing' in search?
Query parsing interprets the raw query string — tokenizing it, identifying field-specific terms (title:foo), boolean operators (AND/OR/NOT), and phrase queries ('exact phrase') — before search execution.