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Author: Barbara McGillivray
Publisher: BRILL
ISBN: 9004260129
Category : Language Arts & Disciplines
Languages : en
Pages : 246
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Book Description
In Methods in Latin Computational Linguistics, Barbara McGillivray presents some of the most significant methodological foundations of the emerging field of Latin Computational Linguistics. The reader will find an overview of the computational resources and tools available for Latin and three corpus case studies covering morpho-syntactic and lexical-semantic aspects of Latin verb valency, as well as quantitative diachronic explorations of the argument realization of Latin prefixed verbs. The computational models and the multivariate data analysis techniques employed are explained with a detailed but accessible language. Barbara McGillivray convincingly shows the challenges and opportunities of combining computational methods and historical language data, and contributes to driving the technological change that is affecting Historical Linguistics and the Humanities.
Author: Barbara McGillivray
Publisher: BRILL
ISBN: 9004260129
Category : Language Arts & Disciplines
Languages : en
Pages : 246
Get Book Here
Book Description
In Methods in Latin Computational Linguistics, Barbara McGillivray presents some of the most significant methodological foundations of the emerging field of Latin Computational Linguistics. The reader will find an overview of the computational resources and tools available for Latin and three corpus case studies covering morpho-syntactic and lexical-semantic aspects of Latin verb valency, as well as quantitative diachronic explorations of the argument realization of Latin prefixed verbs. The computational models and the multivariate data analysis techniques employed are explained with a detailed but accessible language. Barbara McGillivray convincingly shows the challenges and opportunities of combining computational methods and historical language data, and contributes to driving the technological change that is affecting Historical Linguistics and the Humanities.
Author: Barbara McGillivray
Publisher: Springer Nature
ISBN: 3030464938
Category : Language Arts & Disciplines
Languages : en
Pages : 133
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Book Description
This book presents established and state-of-the-art methods in Language Technology (including text mining, corpus linguistics, computational linguistics, and natural language processing), and demonstrates how they can be applied by humanities scholars working with textual data. The landscape of humanities research has recently changed thanks to the proliferation of big data and large textual collections such as Google Books, Early English Books Online, and Project Gutenberg. These resources have yet to be fully explored by new generations of scholars, and the authors argue that Language Technology has a key role to play in the exploration of large-scale textual data. The authors use a series of illustrative examples from various humanistic disciplines (mainly but not exclusively from History, Classics, and Literary Studies) to demonstrate basic and more complex use-case scenarios. This book will be useful to graduate students and researchers in humanistic disciplines working with textual data, including History, Modern Languages, Literary studies, Classics, and Linguistics. This is also a very useful book for anyone teaching or learning Digital Humanities and interested in the basic concepts from computational linguistics, corpus linguistics, and natural language processing.
Author: Nina Tahmasebi
Publisher: Language Science Press
ISBN: 3961103127
Category : Language Arts & Disciplines
Languages : en
Pages : 396
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Book Description
Semantic change — how the meanings of words change over time — has preoccupied scholars since well before modern linguistics emerged in the late 19th and early 20th century, ushering in a new methodological turn in the study of language change. Compared to changes in sound and grammar, semantic change is the least understood. Ever since, the study of semantic change has progressed steadily, accumulating a vast store of knowledge for over a century, encompassing many languages and language families. Historical linguists also early on realized the potential of computers as research tools, with papers at the very first international conferences in computational linguistics in the 1960s. Such computational studies still tended to be small-scale, method-oriented, and qualitative. However, recent years have witnessed a sea-change in this regard. Big-data empirical quantitative investigations are now coming to the forefront, enabled by enormous advances in storage capability and processing power. Diachronic corpora have grown beyond imagination, defying exploration by traditional manual qualitative methods, and language technology has become increasingly data-driven and semantics-oriented. These developments present a golden opportunity for the empirical study of semantic change over both long and short time spans. A major challenge presently is to integrate the hard-earned knowledge and expertise of traditional historical linguistics with cutting-edge methodology explored primarily in computational linguistics. The idea for the present volume came out of a concrete response to this challenge. The 1st International Workshop on Computational Approaches to Historical Language Change (LChange'19), at ACL 2019, brought together scholars from both fields. This volume offers a survey of this exciting new direction in the study of semantic change, a discussion of the many remaining challenges that we face in pursuing it, and considerably updated and extended versions of a selection of the contributions to the LChange'19 workshop, addressing both more theoretical problems — e.g., discovery of "laws of semantic change" — and practical applications, such as information retrieval in longitudinal text archives.
Author: Ruslan Mitkov
Publisher: Oxford University Press
ISBN: 019927634X
Category : Computers
Languages : en
Pages : 808
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Book Description
This handbook of computational linguistics, written for academics, graduate students and researchers, provides a state-of-the-art reference to one of the most active and productive fields in linguistics.
Author: Neamat El Gayar
Publisher: World Scientific
ISBN: 9813229403
Category : Computers
Languages : en
Pages : 286
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Book Description
This book encompasses a collection of topics covering recent advances that are important to the Arabic language in areas of natural language processing, speech and image analysis. This book presents state-of-the-art reviews and fundamentals as well as applications and recent innovations.The book chapters by top researchers present basic concepts and challenges for the Arabic language in linguistic processing, handwritten recognition, document analysis, text classification and speech processing. In addition, it reports on selected applications in sentiment analysis, annotation, text summarization, speech and font analysis, word recognition and spotting and question answering.Moreover, it highlights and introduces some novel applications in vital areas for the Arabic language. The book is therefore a useful resource for young researchers who are interested in the Arabic language and are still developing their fundamentals and skills in this area. It is also interesting for scientists who wish to keep track of the most recent research directions and advances in this area.
Author: Ralph Grishman
Publisher: Cambridge University Press
ISBN: 9780521310383
Category : Computers
Languages : en
Pages : 204
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Book Description
A highly respected introduction to the computer analysis of language. Copyright © Libri GmbH. All rights reserved.
Author: Gard B. Jenset
Publisher: Oxford University Press
ISBN: 0191028010
Category : Language Arts & Disciplines
Languages : en
Pages : 247
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Book Description
This book is an innovative guide to quantitative, corpus-based research in historical and diachronic linguistics. Gard B. Jenset and Barbara McGillivray argue that, although historical linguistics has been successful in using the comparative method, the field lags behind other branches of linguistics with respect to adopting quantitative methods. Here they provide a theoretically agnostic description of a new framework for quantitatively assessing models and hypotheses in historical linguistics, based on corpus data and using case studies to illustrate how this framework can answer research questions in historical linguistics. The authors offer an in-depth explanation and discussion of the benefits of working with quantitative methods, corpus data, and corpus annotation, and the advantages of open and reproducible research. The book will be a valuable resource for graduate students and researchers in historical linguistics, as well as for all those working with linguistic corpora.
Author: Monica Berti
Publisher: Walter de Gruyter GmbH & Co KG
ISBN: 3110596997
Category : Philosophy
Languages : en
Pages : 336
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Book Description
Thanks to the digital revolution, even a traditional discipline like philology has been enjoying a renaissance within academia and beyond. Decades of work have been producing groundbreaking results, raising new research questions and creating innovative educational resources. This book describes the rapidly developing state of the art of digital philology with a focus on Ancient Greek and Latin, the classical languages of Western culture. Contributions cover a wide range of topics about the accessibility and analysis of Greek and Latin sources. The discussion is organized in five sections concerning open data of Greek and Latin texts; catalogs and citations of authors and works; data entry, collection and analysis for classical philology; critical editions and annotations of sources; and finally linguistic annotations and lexical databases. As a whole, the volume provides a comprehensive outline of an emergent research field for a new generation of scholars and students, explaining what is reachable and analyzable that was not before in terms of technology and accessibility.
Author: Emil Hvitfeldt
Publisher: CRC Press
ISBN: 1000461971
Category : Computers
Languages : en
Pages : 402
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Book Description
Text data is important for many domains, from healthcare to marketing to the digital humanities, but specialized approaches are necessary to create features for machine learning from language. Supervised Machine Learning for Text Analysis in R explains how to preprocess text data for modeling, train models, and evaluate model performance using tools from the tidyverse and tidymodels ecosystem. Models like these can be used to make predictions for new observations, to understand what natural language features or characteristics contribute to differences in the output, and more. If you are already familiar with the basics of predictive modeling, use the comprehensive, detailed examples in this book to extend your skills to the domain of natural language processing. This book provides practical guidance and directly applicable knowledge for data scientists and analysts who want to integrate unstructured text data into their modeling pipelines. Learn how to use text data for both regression and classification tasks, and how to apply more straightforward algorithms like regularized regression or support vector machines as well as deep learning approaches. Natural language must be dramatically transformed to be ready for computation, so we explore typical text preprocessing and feature engineering steps like tokenization and word embeddings from the ground up. These steps influence model results in ways we can measure, both in terms of model metrics and other tangible consequences such as how fair or appropriate model results are.
Author: Alexander Gelbukh
Publisher: Springer
ISBN: 3319771167
Category : Computers
Languages : en
Pages : 674
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Book Description
The two-volume set LNCS 10761 + 10762 constitutes revised selected papers from the CICLing 2017 conference which took place in Budapest, Hungary, in April 2017. The total of 90 papers presented in the two volumes was carefully reviewed and selected from numerous submissions. In addition, the proceedings contain 4 invited papers. The papers are organized in the following topical sections: Part I: general; morphology and text segmentation; syntax and parsing; word sense disambiguation; reference and coreference resolution; named entity recognition; semantics and text similarity; information extraction; speech recognition; applications to linguistics and the humanities. Part II: sentiment analysis; opinion mining; author profiling and authorship attribution; social network analysis; machine translation; text summarization; information retrieval and text classification; practical applications.
