AI 용어집
인공지능 완전 사전
QA à Base de Récupération
Systèmes qui récupèrent des réponses pertinentes à partir d'une collection de documents pré-indexés.
QA Génératif
Systèmes qui génèrent des réponses nouvelles à partir de connaissances apprises lors de l'entraînement.
QA sur Base de Connaissances Structurées
Systèmes interrogant des bases de données structurées comme les graphes de connaissances pour fournir des réponses factuelles.
Open Domain QA
Systems capable of answering questions on any topic without predefined domain restrictions.
Conversational QA
Systems that maintain a conversational context and handle multi-turn interactions with the user.
Multi-hop QA
Systems requiring multiple steps of reasoning and information retrieval to compose a complete response.
Real-Time QA
Systems optimized to provide instant responses with minimal latency.
Multimodal QA
Systems handling questions and answers combining text, images, audio and other modalities.
Domain-Specific QA
Specialized and optimized systems for particular domains such as medicine, law, or finance.
Explanatory QA
Systems that provide justifications and evidence for their answers.
Cross-lingual QA
Systems capable of understanding questions in one language and answering in another.
QA by Entity Extraction
Systems specialized in identifying and extracting specific entities like names, dates, or places.
QA by Common Sense Reasoning
Systems using common sense knowledge to answer questions requiring implicit reasoning.
QA by Fact-Checking
Systems specialized in verifying the authenticity and veracity of claims.