Computational and corpus linguistics

In this handbook, renowned scholars from a range of backgrounds provide a state of the art review of key developmental findings in language acquisition.

Many AI (and machine learning) tasks present in dual forms, e.

Metaphor is a topical issue across a number of disciplines, wherever researchers are concerned with how speakers and writers package and process messages.

This book extensively covers the use of graph-based algorithms for natural language processing and information retrieval.

The majority of natural language processing (NLP) is English language processing, and while there is good language technology support for (standard varieties of) English, support for Albanian, Burmese, or Cebuano--and most other languages--remains limited.

Over the past decades, the use of quantitative methods has become almost generalized in all domains of linguistics.

Seit den 1990er Jahren hat sich die Diskurslinguistik in der Germanistischen Sprachwissenschaft als neue Teildisziplin zur Analyse textübergreifender Muster fest etablieren können.

Reversible grammar allows computational models to be built that are equally well suited for the analysis and generation of natural language utterances.

Recent Advances in Example-Based Machine Translation is of relevance to researchers and program developers in the field of Machine Translation and especially Example-Based Machine Translation, bilingual text processing and cross-linguistic information retrieval.

This book advances the growing area of language policy and planning (LPP) by examining the epistemological and theoretical foundations that engendered and sustain the field, drawing on insights and approaches from anthropology, linguistics, economics, political science, and education to create an accessible and inter-disciplinary overview of LPP as a coherent discipline.

The present volume is intended as a reference book on Wikipedia corpus studies, from corpus construction to exploration and analysis.

This book focuses on information literacy for the younger generation of learners and library readers.

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Presenting the digital humanities as both a domain of practice and as a set of methodological approaches to be applied to corpus linguistics and translation, chapters in this volume provide a novel and original framework to triangulate research for pursuing both scientific and educational goals within the digital humanities.

This book integrates current advances in biology, economics of information and linguistics research through applications using agent-based modeling and social network analysis to develop scenarios of communication and language emergence in the social aspects of biological communications.

This book collects research contributions concerning quantitative approaches to characterize originality and universality in language.

This Element offers a concise, accessible, and state-of-the-art introduction to machine learning-based sentiment analysis.

Contrastive studies have experienced a dramatic revival in the last decades.

The volume addresses the role of salience in discourse and provides broad coverage of various perspectives on and functions of discourse salience.

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This book introduces formal semantics techniques for a natural language processing audience.

Corpus linguistics is often regarded as a methodology in its own right, but little attention has been given to the theoretical perspectives from which the subject can be approached.

This SpringerBrief presents the data- information-and-time (DIT) model that precisely clarifies the semantics behind the terms data, information and their relations to the passage of real time.

Children's literature shapes what children learn about the world.

Discourse Processing here is framed as marking up a text with structural descriptions on several levels, which can serve to support many language-processing or text-mining tasks.

Academic vocabulary is in fashion, as witnessed by the increasing number of books published on the topic.

This edited collection draws on case studies from around the world to shed light on the sometimes contentious topic of populism.

Human language acquisition has been studied for centuries, but using computational modeling for such studies is a relatively recent trend.

Modern science is divided into three parts: natural sciences, engineering sciences and humanities.

This book provides readers with a brief account of the history of Language Identification (LI) research and a survey of the features and methods most used in LI literature.

This volume showcases original, agenda-setting studies in the field of learner corpus research of both spoken and written production.

This reader collects and introduces important work in linguistics, computer science, artificial intelligence, and computational linguistics on the use of linguistic devices in natural languages to situate events in time: whether they are past, present, or future; whether they are real or hypothetical; when an event might have occurred, and how long it could have lasted.

The topic addressed in this volume lies within the study of sentence processing, which is one of the major divisions of psycholinguistics.

The ultimate goal of Computational Linguistics is to teach the computer to understand Natural Language.

This book collects and introduces some of the best and most useful work in practical lexicography.