... Graph construction and b-matching for semi-supervised learning. In: Proceedings of the 26th Annual International ... Scalable corpus annotation by graph construction and label propagation. In: Proceedings of the 1st International ...

Our hope is that after reading this book, the reader will walk away with the following: (1) an in-depth knowledge of the current state-of-the-art in graph-based SSL algorithms, and the ability to implement them; (2) the ability to decide on ...

This open access book summarizes the first two decades of the NII Testbeds and Community for Information access Research (NTCIR).

A comprehensive and accessible introduction to statistics in corpus linguistics, covering multiple techniques of quantitative language analysis and data visualisation.

This handbook offers a thorough treatment of the science of linguistic annotation. Leaders in the field guide the reader through the process of modeling, creating an annotation language, building a corpus and evaluating it for correctness.

This book focuses on MapReduce algorithm design, with an emphasis on text processing algorithms common in natural language processing, information retrieval, and machine learning.

The text synthesizes and distills a broad and diverse research literature, linking contemporary machine learning techniques with the field's linguistic and computational foundations.

This open access book provides an overview of the recent advances in representation learning theory, algorithms and applications for natural language processing (NLP).

This is a revised version of the thesis that won the 2015 ACM Doctoral Dissertation Award.

Finally, the book looks at interesting directions for SSL research. The book closes with a discussion of the relationship between semi-supervised learning and transduction.