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Using Large Corpora identifies new data-oriented methods for organizing and analyzing large corpora and describes the potential results that the use of large corpora offers. Today, large corpora consisting of hundreds of millions or even billions of words, along with new empirical and statistical methods for organizing and analyzing these data, promise new insights into the use of language. Already, the data extracted from these large corpora reveal that language use is more flexible and complex than most rule-based systems have tried to account for, providing a basis for progress in the performance of Natural Language Processing systems. Using Large Corpora identifies these new data-oriented methods and describes the potential results that the use of large corpora offers. The research described shows that the new methods may offer solutions to key issues of acquisition (automatically identifying and coding information), coverage (accounting for all of the phenomena in a given domain), robustness (accommodating real data that may be corrupt or not accounted for in the model), and extensibility (applying the model and data to a new domain, text, or problem). There are chapters on lexical issues, issues in syntax, and translation topics, as well discussions of the statistics-based vs. rule-based debate. ACL-MIT Series in Natural Language Processing.
ABOUT THIS BOOK This book is intended for researchers who want to keep abreast of cur rent developments in corpus-based natural language processing. It is not meant as an introduction to this field; for readers who need one, several entry-level texts are available, including those of (Church and Mercer, 1993; Charniak, 1993; Jelinek, 1997). This book captures the essence of a series of highly successful work shops held in the last few years. The response in 1993 to the initial Workshop on Very Large Corpora (Columbus, Ohio) was so enthusias tic that we were encouraged to make it an annual event. The following year, we staged the Second Workshop on Very Large Corpora in Ky oto. As a way of managing these annual workshops, we then decided to register a special interest group called SIGDAT with the Association for Computational Linguistics. The demand for international forums on corpus-based NLP has been expanding so rapidly that in 1995 SIGDAT was led to organize not only the Third Workshop on Very Large Corpora (Cambridge, Mass. ) but also a complementary workshop entitled From Texts to Tags (Dublin). Obviously, the success of these workshops was in some measure a re flection of the growing popularity of corpus-based methods in the NLP community. But first and foremost, it was due to the fact that the work shops attracted so many high-quality papers.
How can you carry out discourse analysis using corpus linguistics? What research questions should I ask? Which methods should you use and when? What is a collocational network or a key cluster? Introducing the major techniques, methods and tools for corpus-assisted analysis of discourse, this book answers these questions and more, showing readers how to best use corpora in their analyses of discourse. Using carefully tailored case studies, each chapter is devoted to a central technique, including frequency, concordancing and keywords, going step by step through the process of applying different analytical procedures. Introducing a wide range of different corpora, from holiday brochures to political debates, the book considers the key debates and latest advances in the field. Fully revised and updated, this new edition includes: - A new chapter on how to conduct research projects in corpus-based discourse analysis - Completely rewritten chapters on collocation and advanced techniques, using a corpus of jihadist propaganda texts and covering topics such as social media and visual analysis - Coverage of major tools, including CQPweb, AntConc, Sketch Engine and #LancsBox - Discussion of newer techniques including the derivation of lockwords and the comparison of multiple data sets for diachronic analysis With exercises, discussion questions and suggested further readings in each chapter, this book is an excellent guide to using corpus linguistics techniques to carry out discourse analysis.
An entirely new follow-up volume providing a detailed account of numerous additional issues, methods, and results that characterize current work in historical linguistics. This brand-new, second volume of The Handbook of Historical Linguistics is a complement to the well-established first volume first published in 2003. It includes extended content allowing uniquely comprehensive coverage of the study of language(s) over time. Though it adds fresh perspectives on several topics previously treated in the first volume, this Handbook focuses on extensions of diachronic linguistics beyond those key issues. This Handbook provides readers with studies of language change whose perspectives range from comparisons of large open vs. small closed corpora, via creolistics and linguistic contact in general, to obsolescence and endangerment of languages. Written by leading scholars in their respective fields, new chapters are offered on matters such as the origin of language, evidence from language for reconstructing human prehistory, invocations of language present in studies of language past, benefits of linguistic fieldwork for historical investigation, ways in which not only biological evolution but also field biology can serve as heuristics for research into the rise and spread of linguistic innovations, and more. Moreover, it: offers novel and broadened content complementing the earlier volume so as to provide the fullest available overview of a wholly engrossing field includes 23 all-new contributed chapters, treating some familiar themes from fresh perspectives but mostly covering entirely new topics features expanded discussion of material from language families other than Indo-European provides a multiplicity of views from numerous specialists in linguistic diachrony. The Handbook of Historical Linguistics, Volume II is an ideal book for undergraduate and graduate students in linguistics, researchers and professional linguists, as well as all those interested in the history of particular languages and the history of language more generally.
Introduces the integration of theoretical and applied translation studies for socially-oriented and data-driven empirical translation research.
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 several adavantages of this approach: (i) Working with such corpora obviates the problems encountered when using Internet search engines in quantitative linguistic research (such as non-transparent ranking algorithms). (ii) Creating a corpus from web data is virtually free. (iii) The size of corpora compiled from the WWW may exceed by several orders of magnitudes the size of language resources offered elsewhere. (iv) The data is locally available to the user, and it can be linguistically post-processed and queried with the tools preferred by her/him. This book addresses the main practical tasks in the creation of web corpora up to giga-token size. Among these tasks are the sampling process (i.e., web crawling) and the usual cleanups including boilerplate removal and removal of duplicated content. Linguistic processing and problems with linguistic processing coming from the different kinds of noise in web corpora are also covered. Finally, the authors show how web corpora can be evaluated and compared to other corpora (such as traditionally compiled corpora).
The first textbook of its kind, Quantitative Corpus Linguistics with R demonstrates how to use the open source programming language R for corpus linguistic analyses. Computational and corpus linguists doing corpus work will find that R provides an enormous range of functions that currently require several programs to achieve – searching and processing corpora, arranging and outputting the results of corpus searches, statistical evaluation, and graphing.
Introduces students to the scientific study of language, using the basic principles of complexity theory.