Download or read book Natural Language Processing for Historical Texts written by Michael Piotrowski and published by Morgan & Claypool Publishers. This book was released on 2012-09-01 with total page 159 pages. Available in PDF, EPUB and Kindle. Book excerpt: More and more historical texts are becoming available in digital form. Digitization of paper documents is motivated by the aim of preserving cultural heritage and making it more accessible, both to laypeople and scholars. As digital images cannot be searched for text, digitization projects increasingly strive to create digital text, which can be searched and otherwise automatically processed, in addition to facsimiles. Indeed, the emerging field of digital humanities heavily relies on the availability of digital text for its studies. Together with the increasing availability of historical texts in digital form, there is a growing interest in applying natural language processing (NLP) methods and tools to historical texts. However, the specific linguistic properties of historical texts -- the lack of standardized orthography, in particular -- pose special challenges for NLP. This book aims to give an introduction to NLP for historical texts and an overview of the state of the art in this field. The book starts with an overview of methods for the acquisition of historical texts (scanning and OCR), discusses text encoding and annotation schemes, and presents examples of corpora of historical texts in a variety of languages. The book then discusses specific methods, such as creating part-of-speech taggers for historical languages or handling spelling variation. A final chapter analyzes the relationship between NLP and the digital humanities. Certain recently emerging textual genres, such as SMS, social media, and chat messages, or newsgroup and forum postings share a number of properties with historical texts, for example, nonstandard orthography and grammar, and profuse use of abbreviations. The methods and techniques required for the effective processing of historical texts are thus also of interest for research in other domains. Table of Contents: Introduction / NLP and Digital Humanities / Spelling in Historical Texts / Acquiring Historical Texts / Text Encoding and Annotation Schemes / Handling Spelling Variation / NLP Tools for Historical Languages / Historical Corpora / Conclusion / Bibliography

Download or read book Natural Language Processing for Historical Texts written by Michael Piotrowski and published by Springer Nature. This book was released on 2022-05-31 with total page 145 pages. Available in PDF, EPUB and Kindle. Book excerpt: More and more historical texts are becoming available in digital form. Digitization of paper documents is motivated by the aim of preserving cultural heritage and making it more accessible, both to laypeople and scholars. As digital images cannot be searched for text, digitization projects increasingly strive to create digital text, which can be searched and otherwise automatically processed, in addition to facsimiles. Indeed, the emerging field of digital humanities heavily relies on the availability of digital text for its studies. Together with the increasing availability of historical texts in digital form, there is a growing interest in applying natural language processing (NLP) methods and tools to historical texts. However, the specific linguistic properties of historical texts -- the lack of standardized orthography, in particular -- pose special challenges for NLP. This book aims to give an introduction to NLP for historical texts and an overview of the state of the art in this field. The book starts with an overview of methods for the acquisition of historical texts (scanning and OCR), discusses text encoding and annotation schemes, and presents examples of corpora of historical texts in a variety of languages. The book then discusses specific methods, such as creating part-of-speech taggers for historical languages or handling spelling variation. A final chapter analyzes the relationship between NLP and the digital humanities. Certain recently emerging textual genres, such as SMS, social media, and chat messages, or newsgroup and forum postings share a number of properties with historical texts, for example, nonstandard orthography and grammar, and profuse use of abbreviations. The methods and techniques required for the effective processing of historical texts are thus also of interest for research in other domains. Table of Contents: Introduction / NLP and Digital Humanities / Spelling in Historical Texts / Acquiring Historical Texts / Text Encoding and Annotation Schemes / Handling Spelling Variation / NLP Tools for Historical Languages / Historical Corpora / Conclusion / Bibliography

Download or read book Named Entity Resolution for Historical Texts written by Audrey Holmes and published by . This book was released on 2019 with total page 34 pages. Available in PDF, EPUB and Kindle. Book excerpt: The field of digital humanities has spurred an increase in applications of computational linguistics to historical documents, but the field remains underdeveloped. Standard natural language processing (NLP) techniques developed using contemporary texts tend to perform poorly when applied to historical documents due to challenges such as spelling variation, semantic shifts, and lack of standard orthography. In this thesis, we compare performance of common Named Entity Recognition (NER) libraries including Stanford CoreNLP, spaCy, and Flair on historical texts. We also present a method for named entity resolution designed specifically for historical texts, which combines domain adapted word embeddings with phonetic and lexical similarities. This has the potential to increase the speed of digitization of historical documents and improve search capabilities across historical corpora. The algorithm is one of the first trained on historical documents and improves upon common approaches to spelling normalization for historical documents using only lexical and/or phonetic similarity. Additionally, we provide a user interface so that scholars without programming expertise can easily use the tools developed in this thesis. Future work will include linking historical named entities to contemporary references and constructing knowledge graphs for historical corpora.

Download or read book Biomedical Natural Language Processing written by Kevin Bretonnel Cohen and published by John Benjamins Publishing Company. This book was released on 2014-02-15 with total page 174 pages. Available in PDF, EPUB and Kindle. Book excerpt: Biomedical Natural Language Processing is a comprehensive tour through the classic and current work in the field. It discusses all subjects from both a rule-based and a machine learning approach, and also describes each subject from the perspective of both biological science and clinical medicine. The intended audience is readers who already have a background in natural language processing, but a clear introduction makes it accessible to readers from the fields of bioinformatics and computational biology, as well. The book is suitable as a reference, as well as a text for advanced courses in biomedical natural language processing and text mining.

Download or read book Natural Language Processing and Text Mining written by Anne Kao and published by Springer Science & Business Media. This book was released on 2007-03-06 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: Natural Language Processing and Text Mining not only discusses applications of Natural Language Processing techniques to certain Text Mining tasks, but also the converse, the use of Text Mining to assist NLP. It assembles a diverse views from internationally recognized researchers and emphasizes caveats in the attempt to apply Natural Language Processing to text mining. This state-of-the-art survey is a must-have for advanced students, professionals, and researchers.

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 Current Issues in Computational Linguistics In Honour of Don Walker written by Antonio Zampolli and published by Springer Science & Business Media. This book was released on 1994-06-30 with total page 596 pages. Available in PDF, EPUB and Kindle. Book excerpt: With this volume in honour of Don Walker, Linguistica Computazionale con tinues the series of special issues dedicated to outstanding personalities who have made a significant contribution to the progress of our discipline and maintained a special collaborative relationship with our Institute in Pisa. I take the liberty of quoting in this preface some of the initiatives Pisa and Don Walker have jointly promoted and developed during our collaboration, because I think that they might serve to illustrate some outstanding features of Don's personality, in particular his capacity for identifying areas of potential convergence among the different scientific communities within our field and establishing concrete forms of coop eration. These initiatives also testify to his continuous and untiring work, dedi cated to putting people into contact and opening up communication between them, collecting and disseminating information, knowledge and resources, and creating shareable basic infrastructures needed for progress in our field. Our collaboration began within the Linguistics in Documentation group of the FID and continued in the framework of the !CCL (International Committee for Computational Linguistics). In 1982 this collaboration was strengthened when, at CO LING in Prague, I was invited by Don to join him in the organization of a series of workshops with participants of the various communities interested in the study, development, and use of computational lexica.

Download or read book Deep Learning for Natural Language Processing written by Stephan Raaijmakers and published by Simon and Schuster. This book was released on 2022-12-20 with total page 294 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explore the most challenging issues of natural language processing, and learn how to solve them with cutting-edge deep learning! Inside Deep Learning for Natural Language Processing you’ll find a wealth of NLP insights, including: An overview of NLP and deep learning One-hot text representations Word embeddings Models for textual similarity Sequential NLP Semantic role labeling Deep memory-based NLP Linguistic structure Hyperparameters for deep NLP Deep learning has advanced natural language processing to exciting new levels and powerful new applications! For the first time, computer systems can achieve "human" levels of summarizing, making connections, and other tasks that require comprehension and context. Deep Learning for Natural Language Processing reveals the groundbreaking techniques that make these innovations possible. Stephan Raaijmakers distills his extensive knowledge into useful best practices, real-world applications, and the inner workings of top NLP algorithms. About the technology Deep learning has transformed the field of natural language processing. Neural networks recognize not just words and phrases, but also patterns. Models infer meaning from context, and determine emotional tone. Powerful deep learning-based NLP models open up a goldmine of potential uses. About the book Deep Learning for Natural Language Processing teaches you how to create advanced NLP applications using Python and the Keras deep learning library. You’ll learn to use state-of the-art tools and techniques including BERT and XLNET, multitask learning, and deep memory-based NLP. Fascinating examples give you hands-on experience with a variety of real world NLP applications. Plus, the detailed code discussions show you exactly how to adapt each example to your own uses! What's inside Improve question answering with sequential NLP Boost performance with linguistic multitask learning Accurately interpret linguistic structure Master multiple word embedding techniques About the reader For readers with intermediate Python skills and a general knowledge of NLP. No experience with deep learning is required. About the author Stephan Raaijmakers is professor of Communicative AI at Leiden University and a senior scientist at The Netherlands Organization for Applied Scientific Research (TNO). Table of Contents PART 1 INTRODUCTION 1 Deep learning for NLP 2 Deep learning and language: The basics 3 Text embeddings PART 2 DEEP NLP 4 Textual similarity 5 Sequential NLP 6 Episodic memory for NLP PART 3 ADVANCED TOPICS 7 Attention 8 Multitask learning 9 Transformers 10 Applications of Transformers: Hands-on with BERT

Download or read book Applied Natural Language Processing in the Enterprise written by Ankur A. Patel and published by "O'Reilly Media, Inc.". This book was released on 2021-05-12 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: NLP has exploded in popularity over the last few years. But while Google, Facebook, OpenAI, and others continue to release larger language models, many teams still struggle with building NLP applications that live up to the hype. This hands-on guide helps you get up to speed on the latest and most promising trends in NLP. With a basic understanding of machine learning and some Python experience, you'll learn how to build, train, and deploy models for real-world applications in your organization. Authors Ankur Patel and Ajay Uppili Arasanipalai guide you through the process using code and examples that highlight the best practices in modern NLP. Use state-of-the-art NLP models such as BERT and GPT-3 to solve NLP tasks such as named entity recognition, text classification, semantic search, and reading comprehension Train NLP models with performance comparable or superior to that of out-of-the-box systems Learn about Transformer architecture and modern tricks like transfer learning that have taken the NLP world by storm Become familiar with the tools of the trade, including spaCy, Hugging Face, and fast.ai Build core parts of the NLP pipeline--including tokenizers, embeddings, and language models--from scratch using Python and PyTorch Take your models out of Jupyter notebooks and learn how to deploy, monitor, and maintain them in production

Download or read book Natural Language Processing for Online Applications written by Peter Jackson and published by John Benjamins Publishing. This book was released on 2007-06-05 with total page 243 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text covers the technologies of document retrieval, information extraction, and text categorization in a way which highlights commonalities in terms of both general principles and practical concerns. It assumes some mathematical background on the part of the reader, but the chapters typically begin with a non-mathematical account of the key issues. Current research topics are covered only to the extent that they are informing current applications; detailed coverage of longer term research and more theoretical treatments should be sought elsewhere. There are many pointers at the ends of the chapters that the reader can follow to explore the literature. However, the book does maintain a strong emphasis on evaluation in every chapter both in terms of methodology and the results of controlled experimentation.

Download or read book Natural Language Processing in Action written by Hannes Hapke and published by Simon and Schuster. This book was released on 2019-03-16 with total page 798 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary Natural Language Processing in Action is your guide to creating machines that understand human language using the power of Python with its ecosystem of packages dedicated to NLP and AI. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Recent advances in deep learning empower applications to understand text and speech with extreme accuracy. The result? Chatbots that can imitate real people, meaningful resume-to-job matches, superb predictive search, and automatically generated document summaries—all at a low cost. New techniques, along with accessible tools like Keras and TensorFlow, make professional-quality NLP easier than ever before. About the Book Natural Language Processing in Action is your guide to building machines that can read and interpret human language. In it, you'll use readily available Python packages to capture the meaning in text and react accordingly. The book expands traditional NLP approaches to include neural networks, modern deep learning algorithms, and generative techniques as you tackle real-world problems like extracting dates and names, composing text, and answering free-form questions. What's inside Some sentences in this book were written by NLP! Can you guess which ones? Working with Keras, TensorFlow, gensim, and scikit-learn Rule-based and data-based NLP Scalable pipelines About the Reader This book requires a basic understanding of deep learning and intermediate Python skills. About the Author Hobson Lane, Cole Howard, and Hannes Max Hapke are experienced NLP engineers who use these techniques in production. Table of Contents PART 1 - WORDY MACHINES Packets of thought (NLP overview) Build your vocabulary (word tokenization) Math with words (TF-IDF vectors) Finding meaning in word counts (semantic analysis) PART 2 - DEEPER LEARNING (NEURAL NETWORKS) Baby steps with neural networks (perceptrons and backpropagation) Reasoning with word vectors (Word2vec) Getting words in order with convolutional neural networks (CNNs) Loopy (recurrent) neural networks (RNNs) Improving retention with long short-term memory networks Sequence-to-sequence models and attention PART 3 - GETTING REAL (REAL-WORLD NLP CHALLENGES) Information extraction (named entity extraction and question answering) Getting chatty (dialog engines) Scaling up (optimization, parallelization, and batch processing)

Download or read book Foundations of Statistical Natural Language Processing written by Christopher Manning and published by MIT Press. This book was released on 1999-05-28 with total page 719 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical approaches to processing natural language text have become dominant in recent years. This foundational text is the first comprehensive introduction to statistical natural language processing (NLP) to appear. The book contains all the theory and algorithms needed for building NLP tools. It provides broad but rigorous coverage of mathematical and linguistic foundations, as well as detailed discussion of statistical methods, allowing students and researchers to construct their own implementations. The book covers collocation finding, word sense disambiguation, probabilistic parsing, information retrieval, and other applications.

Download or read book Getting Started with Natural Language Processing written by Ekaterina Kochmar and published by Simon and Schuster. This book was released on 2022-11-15 with total page 454 pages. Available in PDF, EPUB and Kindle. Book excerpt: Hit the ground running with this in-depth introduction to the NLP skills and techniques that allow your computers to speak human. In Getting Started with Natural Language Processing you’ll learn about: Fundamental concepts and algorithms of NLP Useful Python libraries for NLP Building a search algorithm Extracting information from raw text Predicting sentiment of an input text Author profiling Topic labeling Named entity recognition Getting Started with Natural Language Processing is an enjoyable and understandable guide that helps you engineer your first NLP algorithms. Your tutor is Dr. Ekaterina Kochmar, lecturer at the University of Bath, who has helped thousands of students take their first steps with NLP. Full of Python code and hands-on projects, each chapter provides a concrete example with practical techniques that you can put into practice right away. If you’re a beginner to NLP and want to upgrade your applications with functions and features like information extraction, user profiling, and automatic topic labeling, this is the book for you. About the technology From smart speakers to customer service chatbots, apps that understand text and speech are everywhere. Natural language processing, or NLP, is the key to this powerful form of human/computer interaction. And a new generation of tools and techniques make it easier than ever to get started with NLP! About the book Getting Started with Natural Language Processing teaches you how to upgrade user-facing applications with text and speech-based features. From the accessible explanations and hands-on examples in this book you’ll learn how to apply NLP to sentiment analysis, user profiling, and much more. As you go, each new project builds on what you’ve previously learned, introducing new concepts and skills. Handy diagrams and intuitive Python code samples make it easy to get started—even if you have no background in machine learning! What's inside Fundamental concepts and algorithms of NLP Extracting information from raw text Useful Python libraries Topic labeling Building a search algorithm About the reader You’ll need basic Python skills. No experience with NLP required. About the author Ekaterina Kochmar is a lecturer at the Department of Computer Science of the University of Bath, where she is part of the AI research group. Table of Contents 1 Introduction 2 Your first NLP example 3 Introduction to information search 4 Information extraction 5 Author profiling as a machine-learning task 6 Linguistic feature engineering for author profiling 7 Your first sentiment analyzer using sentiment lexicons 8 Sentiment analysis with a data-driven approach 9 Topic analysis 10 Topic modeling 11 Named-entity recognition

Download or read book Unveiling the Forgotten written by Shekhar Mohammad Hassan and published by BookRix. This book was released on 2024-09-09 with total page 57 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the dim glow of a digitized screen, historians are unlocking secrets from the past with unprecedented precision. Imagine AI-powered tools unearthing hidden patterns in centuries-old manuscripts or simulating ancient battles with such rich details that history comes alive in ways we have never seen before. This is no longer science-fiction — this is the transformative power of Artificial Intelligence in historical research and writing. From enhancing the accessibility of fragile texts through advanced Optical Character Recognition (OCR) to unraveling complex datasets with machine learning algorithms, AI is revolutionizing the field of history. Picture historians effortlessly analyzing vast archives, revealing insights into historical trends and societal shifts that were previously buried under layers of time. This research paper delves deep into the cutting-edge applications of AI in historical scholarship, highlighting its profound impact on data analysis, archival research, and historical simulations. Discover how AI is reshaping our understanding of the past and why embracing these technological advancements are crucial for the future of historical inquiry. Dive into a world where past meets future, and see how AI is setting the stage for a new era of historical exploration.

Download or read book Applied Natural Language Processing written by Philip M. McCarthy and published by IGI Global. This book was released on 2012 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book offers a description of ANLP: what it is, what it does; and where it's going, including defining the role of ANLP within NLP, and alongside other disciplines such as linguistics, computer science, and cognitive science"--Provided by publisher.

Download or read book Modern Information Technology and IT Education written by Vladimir Sukhomlin and published by Springer Nature. This book was released on 2021-06-08 with total page 332 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 12th International Conference on Modern Information Technology and IT Education, held in Moscow, Russia, in November 2017. The 30 papers presented were carefully reviewed and selected from 126 submissions. The papers are organized according to the following topics: IT-education: methodology, methodological support; e-learning and IT in education; educational resources and best practices of IT-education; research and development in the field of new IT and their applications; scientific software in education and science; school education in computer science and ICT; economic informatics.

Download or read book Ancient Manuscripts in Digital Culture written by David Hamidović and published by BRILL. This book was released on 2019-05-20 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: Ancient Manuscripts in Digital Culture presents an overview of the digital turn in Ancient Jewish and Christian manuscripts visualisation, data mining and communication. Edited by David Hamidović, Claire Clivaz and Sarah Bowen Savant, it gathers together the contributions of seventeen scholars involved in Biblical, Early Jewish and Christian studies. The volume attests to the spreading of digital humanities in these fields and presents fundamental analysis of the rise of visual culture as well as specific test-cases concerning ancient manuscripts. Sophisticated visualisation tools, stylometric analysis, teaching and visual data, epigraphy and visualisation belong notably to the varied overview presented in the volume.