Download or read book Word Embeddings Reliability Semantic Change written by J. Hellrich and published by IOS Press. This book was released on 2019-08-08 with total page 190 pages. Available in PDF, EPUB and Kindle. Book excerpt: Word embeddings are a form of distributional semantics increasingly popular for investigating lexical semantic change. However, typical training algorithms are probabilistic, limiting their reliability and the reproducibility of studies. Johannes Hellrich investigated this problem both empirically and theoretically and found some variants of SVD-based algorithms to be unaffected. Furthermore, he created the JeSemE website to make word embedding based diachronic research more accessible. It provides information on changes in word denotation and emotional connotation in five diachronic corpora. Finally, the author conducted two case studies on the applicability of these methods by investigating the historical understanding of electricity as well as words connected to Romanticism. They showed the high potential of distributional semantics for further applications in the digital humanities.
Download or read book Supervised Machine Learning for Text Analysis in R written by Emil Hvitfeldt and published by CRC Press. This book was released on 2021-10-22 with total page 402 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Current Methods in Historical Semantics written by Kathryn Allan and published by Walter de Gruyter. This book was released on 2011-12-23 with total page 357 pages. Available in PDF, EPUB and Kindle. Book excerpt: Innovative, data-driven methods provide more rigorous and systematic evidence for the description and explanation of diachronic semantic processes. The volume systematises, reviews, and promotes a range of empirical research techniques and theoretical perspectives that currently inform work across the discipline of historical semantics. In addition to emphasising the use of new technology, the potential of current theoretical models (e.g. within variationist, sociolinguistic or cognitive frameworks) is explored along the way.
Download or read book Historical Semantics and Cognition written by Andreas Blank and published by Walter de Gruyter. This book was released on 2013-03-25 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: Contains revised papers from a September 1996 symposium which provided a forum for synchronically and diachronically oriented scholars to exchange ideas and for American and European cognitive linguists to confront representatives of different directions in European structural semantics. Papers are in sections on theories and models, descriptive categories, and case studies, and examine areas such as cognitive and structural semantics, diachronic prototype semantics, synecdoche as a cognitive and communicative strategy, and intensifiers as targets and sources of semantic change.
Download or read book Regularity in Semantic Change written by Elizabeth Closs Traugott and published by Cambridge University Press. This book was released on 2005-03-24 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt: This new and important study of semantic change examines the various ways in which new meanings arise through language use, especially the ways in which speakers and writers experiment with uses of words and constructions. Drawing on extensive research from over a thousand years of English and Japanese textual history, Traugott and Dasher show that most changes in meaning originate in and are motivated by the associative flow of speech and conceptual metonymy.
Download or read book Cross Lingual Word Embeddings written by Anders Søgaard and published by Morgan & Claypool Publishers. This book was released on 2019-06-04 with total page 134 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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. Being able to bridge this digital divide is important for scientific and democratic reasons but also represents an enormous growth potential. A key challenge for this to happen is learning to align basic meaning-bearing units of different languages. In this book, the authors survey and discuss recent and historical work on supervised and unsupervised learning of such alignments. Specifically, the book focuses on so-called cross-lingual word embeddings. The survey is intended to be systematic, using consistent notation and putting the available methods on comparable form, making it easy to compare wildly different approaches. In so doing, the authors establish previously unreported relations between these methods and are able to present a fast-growing literature in a very compact way. Furthermore, the authors discuss how best to evaluate cross-lingual word embedding methods and survey the resources available for students and researchers interested in this topic.
Download or read book Embeddings in Natural Language Processing written by Mohammad Taher Pilehvar and published by Morgan & Claypool Publishers. This book was released on 2020-11-13 with total page 177 pages. Available in PDF, EPUB and Kindle. Book excerpt: Embeddings have undoubtedly been one of the most influential research areas in Natural Language Processing (NLP). Encoding information into a low-dimensional vector representation, which is easily integrable in modern machine learning models, has played a central role in the development of NLP. Embedding techniques initially focused on words, but the attention soon started to shift to other forms: from graph structures, such as knowledge bases, to other types of textual content, such as sentences and documents. This book provides a high-level synthesis of the main embedding techniques in NLP, in the broad sense. The book starts by explaining conventional word vector space models and word embeddings (e.g., Word2Vec and GloVe) and then moves to other types of embeddings, such as word sense, sentence and document, and graph embeddings. The book also provides an overview of recent developments in contextualized representations (e.g., ELMo and BERT) and explains their potential in NLP. Throughout the book, the reader can find both essential information for understanding a certain topic from scratch and a broad overview of the most successful techniques developed in the literature.
Download or read book Diachronic Semantics written by Dirk Geeraerts and published by . This book was released on 1990 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book The Oxford Handbook of Computational Linguistics written by Ruslan Mitkov and published by Oxford University Press. This book was released on 2004 with total page 808 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book The Architecture of Concepts written by Peter de Bolla and published by Fordham Univ Press. This book was released on 2013-12-02 with total page 413 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Architecture of Concepts proposes a radically new way of understanding the history of ideas. Taking as its example human rights, it develops a distinctive kind of conceptual analysis that enables us to see with precision how the concept of human rights was formed in the eighteenth century. The first chapter outlines an innovative account of concepts as cultural entities. The second develops an original methodology for recovering the historical formation of the concept of human rights based on data extracted from digital archives. This enables us to track the construction of conceptual architectures over time. Having established the architecture of the concept of human rights, the book then examines two key moments in its historical formation: the First Continental Congress in 1775 and the publication of Tom Paine’s Rights of Man in 1792. Arguing that we have yet to fully understand or appreciate the consequences of the eighteenth-century invention of the concept “rights of man,” the final chapter addresses our problematic contemporary attempts to leverage human rights as the most efficacious way of achieving universal equality.
Download or read book Computational approaches to semantic change written by Nina Tahmasebi and published by Language Science Press. This book was released on 2021-08-30 with total page 396 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Language Change written by Jean Aitchison and published by Cambridge University Press. This book was released on 2001 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is a lucid and up-to-date overview of language change. It discusses where our evidence about language change comes from, how and why changes happen, and how languages begin and end. It considers both changes which occurred long ago, and those currently in progress. It does this within the framework of one central question - is language change a symptom of progress or decay? It concludes that language is neither progressing nor decaying, but that an understanding of the factors surrounding change is essential for anyone concerned about language alteration. For this substantially revised third edition, Jean Aitchison has included two new chapters on change of meaning and grammaticalization. Sections on new methods of reconstruction and ongoing chain shifts in Britain and America have also been added as well as over 150 new references. The work remains non-technical in style and accessible to readers with no previous knowledge of linguistics.
Download or read book Representation Learning for Natural Language Processing written by Zhiyuan Liu and published by Springer Nature. This book was released on 2020-07-03 with total page 319 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book provides an overview of the recent advances in representation learning theory, algorithms and applications for natural language processing (NLP). It is divided into three parts. Part I presents the representation learning techniques for multiple language entries, including words, phrases, sentences and documents. Part II then introduces the representation techniques for those objects that are closely related to NLP, including entity-based world knowledge, sememe-based linguistic knowledge, networks, and cross-modal entries. Lastly, Part III provides open resource tools for representation learning techniques, and discusses the remaining challenges and future research directions. The theories and algorithms of representation learning presented can also benefit other related domains such as machine learning, social network analysis, semantic Web, information retrieval, data mining and computational biology. This book is intended for advanced undergraduate and graduate students, post-doctoral fellows, researchers, lecturers, and industrial engineers, as well as anyone interested in representation learning and natural language processing.
Download or read book Speech Language Processing written by Dan Jurafsky and published by Pearson Education India. This book was released on 2000-09 with total page 912 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Computational Processing of the Portuguese Language written by Paulo Quaresma and published by Springer Nature. This book was released on 2020-02-24 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 14th International Conference on Computational Processing of the Portuguese Language, PROPOR 2020, held in Evora, Portugal, in March 2020. The 36 full papers presented together with 5 short papers were carefully reviewed and selected from 70 submissions. They are grouped in topical sections on speech processing; resources and evaluation; natural language processing applications; semantics; natural language processing tasks; and multilinguality.
Download or read book Bartlett s Roget s Thesaurus written by and published by Little Brown. This book was released on 2003-09-02 with total page 1468 pages. Available in PDF, EPUB and Kindle. Book excerpt: Supplies synonyms and antonyms for words in over 800 categories, arranged thematically, providing information on parts of speech, cross-references, and including quotations that use the featured word.
Download or read book Real World Natural Language Processing written by Masato Hagiwara and published by Simon and Schuster. This book was released on 2021-12-14 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: Voice assistants, automated customer service agents, and other cutting-edge human-to-computer interactions rely on accurately interpreting language as it is written and spoken. Real-world Natural Language Processing teaches you how to create practical NLP applications without getting bogged down in complex language theory and the mathematics of deep learning. In this engaging book, you''ll explore the core tools and techniques required to build a huge range of powerful NLP apps. about the technology Natural language processing is the part of AI dedicated to understanding and generating human text and speech. NLP covers a wide range of algorithms and tasks, from classic functions such as spell checkers, machine translation, and search engines to emerging innovations like chatbots, voice assistants, and automatic text summarization. Wherever there is text, NLP can be useful for extracting meaning and bridging the gap between humans and machines. about the book Real-world Natural Language Processing teaches you how to create practical NLP applications using Python and open source NLP libraries such as AllenNLP and Fairseq. In this practical guide, you''ll begin by creating a complete sentiment analyzer, then dive deep into each component to unlock the building blocks you''ll use in all different kinds of NLP programs. By the time you''re done, you''ll have the skills to create named entity taggers, machine translation systems, spelling correctors, and language generation systems. what''s inside Design, develop, and deploy basic NLP applications NLP libraries such as AllenNLP and Fairseq Advanced NLP concepts such as attention and transfer learning about the reader Aimed at intermediate Python programmers. No mathematical or machine learning knowledge required. about the author Masato Hagiwara received his computer science PhD from Nagoya University in 2009, focusing on Natural Language Processing and machine learning. He has interned at Google and Microsoft Research, and worked at Baidu Japan, Duolingo, and Rakuten Institute of Technology. He now runs his own consultancy business advising clients, including startups and research institutions.
