This book provides an overview of the fundamentals of Automatic Question Generation (AQG) for computational linguistics researchers, test developers, and educators. The author presents a variety of AQG system architectures, including generating questions from syntactic analyses, semantic resources, neural architectures, ontologies and knowledge graphs, and large language models. The advantages and pitfalls of a variety of AQG evaluation methods, including multi-aspect ratings by human experts, end-users, as well as crowd-sourcing and automatic evaluation techniques are discussed. The book also provides a roadmap of options for AQG targeted orientation, content selection, and focusing decisions. Machine learning opportunities for training systems to generate questions based on human-generated examples are also explored. This book offers greater depth and breadth than previous surveys of AQG. Readers will gain a comprehensive knowledge of current research, examples of applications of AQG, and inspiration for future directions for innovation and application.
Produkteigenschaften
- Artikelnummer: 9783031920745
- Medium: Buch
- ISBN: 978-3-031-92074-5
- Verlag: Springer
- Erscheinungstermin: 06.07.2026
- Sprache(n): Englisch
- Auflage: Erscheinungsjahr 2026
- Serie: Synthesis Lectures on Human Language Technologies
- Produktform: Kartoniert
- Seiten: 180
- Format (B x H): 168 x 240 mm
- Ausgabetyp: Kein, Unbekannt
