Query Understanding
Intent classification, spelling and segmentation, expansion, rewriting, and conversational query resolution.
7concepts
133flashcards
50minutes of reading
- 01 Query Autocompletion Proposing full queries from a typed prefix within the gap between two keystrokes, from the most-popular-completion baseline and compressed top-k tries to personalised and generative completion, and the harms of suggesting things people did not ask for.
- 02 Query Entity Recognition and Linking Finding the entity mentions in a two- or three-word query and resolving each to a knowledge-base identifier, under a latency budget measured in milliseconds and with almost no context to disambiguate from.
- 03 Query Intent and Taxonomies The same string can be three different requests, and classifying which one determines whether the right answer is a document, an entity, an action, or a generated response.
- 04 Spelling Correction and Query Segmentation Fixing what the user typed before matching it, where the hard part is not generating candidates but deciding whether the original was wrong at all.
- 05 Conversational Query Rewriting Turning a context-dependent follow-up into a self-contained query, which is what lets a stateless retriever serve a stateful conversation.
- 06 Parsing Queries into Structured Filters Turning a free-text query into attribute constraints and residual text that a structured index can execute exactly, from CRF query tagging to schema-constrained LLM parsing, and why negation is the case that makes parsing worth its cost.
- 07 Query Expansion and Pseudo-Relevance Feedback Adding terms to a query to bridge vocabulary mismatch, and the drift failure that occurs when the terms are harvested from results that were wrong to begin with.