Course Description
Understanding and improving user queries. Classic query expansion: pseudo-relevance feedback, thesaurus expansion, WordNet. Neural query expansion: using LLMs to generate synonyms, related terms, and alternative phrasings. The Scolta approach: LLM-based query expansion that improves BM25 recall without vector infrastructure. Query classification: navigational, informational, transactional. Spelling correction and fuzzy matching. Query suggestion and autocomplete. Students implement and evaluate a query expansion system, comparing classic and neural approaches on the same query set.