Human Language Technologies

SERIES EDITOR: Graeme Hirst, University of Toronto
The series publishes topics relating to natural language processing, computational linguistics, information retrieval, and spoken language understanding. Emphasis is on important new techniques, on new applications, and on topics that combine two or more HLT subfields.

Series ISSN: 1947-4040 (print) 1947-4059 (electronic)

	Argumentation Mining Manfred Stede, Jodi Schneider Argumentation mining is an application of natural language processing (NLP) that emerged a few years ago and has recently enjoyed considerable popularity, as demonstrated by a series of international workshops and by a rising number of publications a… Publication Date: December, 2018 Read More
	Quality Estimation for Machine Translation Lucia Specia, Carolina Scarton, Gustavo Henrique Paetzold Many applications within natural language processing involve performing text-to-text transformations, i.e., given a text in natural language as input, systems are required to produce a version of this text (e.g., a translation), also in natural langu… Publication Date: September, 2018 Read More
	Natural Language Processing for Social Media, Second Edition Atefeh Farzindar, Diana Inkpen In recent years, online social networking has revolutionized interpersonal communication. The newer research on language analysis in social media has been increasingly focusing on the latter’s impact on our daily lives, both on a personal and a profe… Publication Date: December, 2017 Read More
	Automatic Text Simplification Horacio Saggion Thanks to the availability of texts on the Web in recent years, increased knowledge and information have been made available to broader audiences. However, the way in which a text is written (its vocabulary, its syntax) can be difficult to read and u… Publication Date: April, 2017 Read More
	Neural Network Methods for Natural Language Processing Yoav Goldberg Neural networks are a family of powerful machine learning models. This book focuses on the application of neural network models to natural language data. The first half of the book (Parts I and II) covers the basics of supervised machine learning and… Publication Date: April, 2017 Read More
	Syntax-based Statistical Machine Translation Philip Williams, Rico Sennrich, Matt Post, Philipp Koehn This unique book provides a comprehensive introduction to the most popular syntax-based statistical machine translation models, filling a gap in the current literature for researchers and developers in human language technologies. While phrase-based… Publication Date: August, 2016 Read More
	Domain-Sensitive Temporal Tagging Jannik Stroetgen, Michael Gertz This book covers the topic of temporal tagging, the detection of temporal expressions and the normalizationof their semantics to some standard format. It places a special focus on the challenges and opportunities of domain-sensitive temporal tagging…. Publication Date: July, 2016 Read More
	Linked Lexical Knowledge Bases Iryna Gurevych, Judith Eckle-Kohler, Michael Matuschek This book conveys the fundamentals of Linked Lexical Knowledge Bases (LLKB) and sheds light on their different aspects from various perspectives, focusing on their construction and use in natural language processing (NLP). It characterizes a wide ran… Publication Date: July, 2016 Read More
	Bayesian Analysis in Natural Language Processing Shay Cohen Natural language processing (NLP) went through a profound transformation in the mid-1980s when it shifted to make heavy use of corpora and data-driven techniques to analyze language. Since then, the use of statistical techniques in NLP has evolved in… Publication Date: June, 2016 Read More
	Metaphor Tony Veale, Ekaterina Shutova, Beata Beigman Klebanov This book is a comprehensive approach to the computational treatment of metaphor and its figurative brethren (simile, analogy, and conceptual blending) without shying away from their cognitive and philosophical dimensions. While stopping by significa… Publication Date: February, 2016 Read More
	Essentials of Game Theory (E-Book Only) Kevin Leyton-Brown, Yoav Shoham Game theory is the mathematical study of interaction among independent, self-interested agents. The audience for game theory has grown dramatically in recent years, and now spans disciplines as diverse as political science, biology, psychology, econo… Publication Date: 01/01/2008 Read More
	Grammatical Inference for Computational Linguistics Jeffrey Heinz, Colin de la Higuera, Menno van Zaanen This book provides a thorough introduction to the subfield of theoretical computer science known as grammatical inference from a computational linguistic perspective. Grammatical inference provides principled methods for developing computationally so… Publication Date: October, 2015 Read More
	Automatic Detection of Verbal Deception Eileen Fitzpatrick, Joan Bachenko, Tommaso Fornaciari A growing field in computer applications is the use of algorithms to spot the lie. The most promising area within this field is the analysis of the language of the liar since speakers effectively control only the meaning they wish to convey, but not … Publication Date: September, 2015 Read More
	Semantic Similarity from Natural Language and Ontology Analysis Sebastien Harispe, Sylvie Ranwez, Stefan Janaqi, Jacky Montmain Artificial Intelligence federates numerous scientific fields in the aim of developing machines able to assist human operators performing complex treatments; most of which demand high cognitive skills (e.g. learning or decision processes). Central to … Publication Date: May, 2015 Read More
	Learning to Rank for Information Retrieval and Natural Language Processing, Second Edition Hang Li, Learning to rank refers to machine learning techniques for training a model in a ranking task. Learning to rank is useful for many applications in information retrieval, natural language processing, and data mining. Intensive studies have been conduc… Publication Date: 10/01/2014 Read More
	Ontology-Based Interpretation of Natural Language Philipp Cimiano, Christina Unger, John McCrae For humans, understanding a natural language sentence or discourse is so effortless that we hardly ever think about it. For machines, however, the task of interpreting natural language, especially grasping meaning beyond the literal content, has prov… Publication Date: 03/01/2014 Read More
	Automated Grammatical Error Detection for Language Learners, Second Edition Claudia Leacock, Martin Chodorow, Michael Gamon, Joel Tetreault, It has been estimated that over a billion people are using or learning English as a second or foreign language, and the numbers are growing not only for English but for other languages as well. These language learners provide a burgeoning market for … Publication Date: 02/01/2014 Read More
	Web Corpus Construction Roland Schafer, Felix Bildhauer The World Wide Web constitutes the largest existing source of texts written in a great variety of languages. A feasible and sound way of exploiting this data for linguistic research is to compile a static corpus for a given language. There are severa… Publication Date: 07/01/2013 Read More
	Recognizing Textual Entailment Ido Dagan, Dan Roth, Fabio Massimo Zanzotto, Mark Sammons In the last few years, a number of NLP researchers have developed and participated in the task of Recognizing Textual Entailment (RTE). This task encapsulates Natural Language Understanding capabilities within a very simple interface: recognizing wh… Publication Date: 07/01/2013 Read More
	Linguistic Fundamentals for Natural Language Processing Emily M. Bender, Many NLP tasks have at their core a subtask of extracting the dependencies (who did what to whom) from natural language sentences. This task can be understood as the inverse of the problem solved in different ways by diverse human languages, namely, … Publication Date: 06/01/2013 Read More