Semisupervised Learning for Computational Linguistics

Explore the cutting-edge world of computational linguistics with "Semisupervised Learning for Computational Linguistics" by Steven Abney. Published in 2007 by Taylor & Francis, this insightful hardback spans 322 pages, providing a comprehensive examination of the theory and practical applications of semisupervised learning techniques.

Delve into essential natural language processing methods, including self-training and co-training, as well as influential machine learning techniques such as perceptrons, boosting, SVMs, and the innovative null-category noise model. This book is an invaluable resource for students and educators involved in higher studies of computational linguistics and related fields.

Whether you're looking to enhance your understanding of statistics, programming, or engineering in linguistics, Steven Abney's expert guidance makes this book an indispensable addition to your collection.