Practical Natural Language Processing

《語法學習手冊》嚴格依據教育bu和國家語委聯合發布的《國際中文教育中文水平等級標準》“附錄A（規範性）語法等級大綱”（以下簡稱“語法等級大綱”）進行編寫，是面向中文學習者的應用型學習手冊。本書遵循“以學習者為中心”的教育理念，倡導語法自然習得。《語法學習手冊》分初等、中等、高等三個分冊，分別對應“語法等級大綱”初等、中等和高等的語法點。書中對“語法等級大綱”的語法點進行了拆分或合並，圍繞“基本語義及用法”“典型例句和對話”“補充例句”“結構特點”“小提示”等幾個維度對每個語法點進行詳細說明。本書從教學實際出發，力求為國際中文語法學習與教學提供一定的參照與支持。本書為高等分冊，對高等水平學習者的語法學習提供參考。Grammar Learning Manual, a practical learning manual for students of Chinese language, is compiled in strict accordance with the “Appendix A (Normative Grammar Grading Outline)” (hereinafter referred to as “Grammar Grading Outline”) of Chinese Proficiency Grading Standards for International Chinese Language Education, which is jointly issued by the Ministry of Education and the State Language Commission. This book observes the “student-centered” education idea, and advocates the natural acquisition of grammar. Grammar Learning Manualis divided into the elementary, intermediate and advanced levels, respectively corresponding to the grammar points in the “Grammar Grading Outline”. In

The Bloomsbury Handbook to the Digital Humanities reconsiders key debates, methods, possibilities, and failings from across the digital humanities, offering a timely interrogation of the present and future of the arts and humanities in the digital age. Comprising 43 essays from some of the field’s leading scholars and practitioners, this comprehensive collection examines, among its many subjects, the emergence and ongoing development of DH, postcolonial digital humanities, feminist digital humanities, race and DH, multilingual digital humanities, media studies as DH, the failings of DH, critical digital humanities, the future of text encoding, cultural analytics, natural language processing, open access and digital publishing, digital cultural heritage, archiving and editing, sustainability, DH pedagogy, labour, artificial intelligence, the cultural economy, and the role of the digital humanities in climate change. The Bloomsbury Handbook to the Digital Humanities:Surveys key contempo

In Deep Learning with Python, Second Edition, updated from the original bestseller with over 50% new content, you'll explore challenging concepts and practice applications in computer vision, natural-language processing, and generative models. The bestseller revised Deep Learning with Python, Second Edition is a comprehensive introduction to the field of deep learning using Python and the powerful Keras library, written by the creator of Keras himself. This revised edition has been updated with new chapters, new tools, and cutting-edge techniques drawn from the latest research. In Deep Learning with Python, Second Edition, updated from the original bestseller with over 50% new content, you'll explore challenging concepts and practice applications in computer vision, natural-language processing, and generative models, building your understanding through practical examples and intuitive explanations that make the complexities of deep learning easily accessible. Purchase of the print book

Deep learning on graphs has become one of the hottest topics in machine learning. The book consists of four parts to best accommodate our readers with diverse backgrounds and purposes of reading. Part 1 introduces basic concepts of graphs and deep learning; Part 2 discusses the most established methods from the basic to advanced settings; Part 3 presents the most typical applications including natural language processing, computer vision, data mining, biochemistry and healthcare; and Part 4 describes advances of methods and applications that tend to be important and promising for future research. The book is self-contained, making it accessible to a broader range of readers including (1) senior undergraduate and graduate students; (2) practitioners and project managers who want to adopt graph neural networks into their products and platforms; and (3) researchers without a computer science background who want to use graph neural networks to advance their disciplines.

This groundbreaking work offers a first-of-its-kind overview of legal informatics, the academic discipline underlying the technological transformation and economics of the legal industry. Edited by Daniel Martin Katz, Ron Dolin, and Michael J. Bommarito, and featuring contributions from more than two dozen academic and industry experts, chapters cover the history and principles of legal informatics and background technical concepts – including natural language processing and distributed ledger technology. The volume also presents real-world case studies that offer important insights into document review, due diligence, compliance, case prediction, billing, negotiation and settlement, contracting, patent management, legal research, and online dispute resolution. Written for both technical and non-technical readers, Legal Informatics is the ideal resource for anyone interested in identifying, understanding, and executing opportunities in this exciting field.

Turning text into valuable information is essential for businesses looking to gain a competitive advantage. With recent improvements in natural language processing (NLP), users now have many options f

Text is everywhere, and it is a fantastic resource for social scientists. However, because it is so abundant, and because language is so variable, it is often difficult to extract the information we want. There is a whole subfield of AI concerned with text analysis (natural language processing). Many of the basic analysis methods developed are now readily available as Python implementations. This Element will teach you when to use which method, the mathematical background of how it works, and the Python code to implement it.

An essential text on practical application, theory and simulation, written by an international coalition of experts in the field and edited by the authors of Colloidal Suspension Rheology. This up-to-date work builds upon the prior work as a valuable guide to formulation and processing, as well as fundamental rheology of colloidal suspensions. Thematically, theory and simulation are connected to industrial application by consideration of colloidal interactions, particle properties, and suspension microstructure. Important classes of model suspensions including gels, glasses and soft particles are covered so as to develop a deeper understanding of industrial systems ranging from carbon black slurries, paints and coatings, asphalt, cement, and mine tailings, to natural suspensions such as biocolloids, protein solutions, and blood. Systematically presenting the established facts in this multidisciplinary field, this book is the perfect aid for academic researchers, graduate students, and

Sentiment analysis is the computational study of people's opinions, sentiments, emotions, moods, and attitudes. This fascinating problem offers numerous research challenges, but promises insight useful to anyone interested in opinion analysis and social media analysis. This comprehensive introduction to the topic takes a natural-language-processing point of view to help readers understand the underlying structure of the problem and the language constructs commonly used to express opinions, sentiments, and emotions. The book covers core areas of sentiment analysis and also includes related topics such as debate analysis, intention mining, and fake-opinion detection. It will be a valuable resource for researchers and practitioners in natural language processing, computer science, management sciences, and the social sciences. In addition to traditional computational methods, this second edition includes recent deep learning methods to analyze and summarize sentiments and opinions, and als

Deep learning is revolutionizing how machine translation systems are built today. This book introduces the challenge of machine translation and evaluation - including historical, linguistic, and applied context -- then develops the core deep learning methods used for natural language applications. Code examples in Python give readers a hands-on blueprint for understanding and implementing their own machine translation systems. The book also provides extensive coverage of machine learning tricks, issues involved in handling various forms of data, model enhancements, and current challenges and methods for analysis and visualization. Summaries of the current research in the field make this a state-of-the-art textbook for undergraduate and graduate classes, as well as an essential reference for researchers and developers interested in other applications of neural methods in the broader field of human language processing.

This book is an advanced introduction to semantics that presents this crucial component of human language through the lens of the 'Meaning-Text' theory - an approach that treats linguistic knowledge as a huge inventory of correspondences between thought and speech. Formally, semantics is viewed as an organized set of rules that connect a representation of meaning (Semantic Representation) to a representation of the sentence (Deep-Syntactic Representation). The approach is particularly interesting for computer assisted language learning, natural language processing and computational lexicography, as our linguistic rules easily lend themselves to formalization and computer applications. The model combines abstract theoretical constructions with numerous linguistic descriptions, as well as multiple practice exercises that provide a solid hands-on approach to learning how to describe natural language semantics.

With its intuitive yet rigorous approach to machine learning, this text provides students with the fundamental knowledge and practical tools needed to conduct research and build data-driven products. The authors prioritize geometric intuition and algorithmic thinking, and include detail on all the essential mathematical prerequisites, to offer a fresh and accessible way to learn. Practical applications are emphasized, with examples from disciplines including computer vision, natural language processing, economics, neuroscience, recommender systems, physics, and biology. Over 300 color illustrations are included and have been meticulously designed to enable an intuitive grasp of technical concepts, and over 100 in-depth coding exercises (in Python) provide a real understanding of crucial machine learning algorithms. A suite of online resources including sample code, data sets, interactive lecture slides, and a solutions manual are provided online, making this an ideal text both for grad

This book is an advanced introduction to semantics that presents this crucial component of human language through the lens of the 'Meaning-Text' theory - an approach that treats linguistic knowledge as a huge inventory of correspondences between thought and speech. Formally, semantics is viewed as an organized set of rules that connect a representation of meaning (Semantic Representation) to a representation of the sentence (Deep-Syntactic Representation). The approach is particularly interesting for computer assisted language learning, natural language processing and computational lexicography, as our linguistic rules easily lend themselves to formalization and computer applications. The model combines abstract theoretical constructions with numerous linguistic descriptions, as well as multiple practice exercises that provide a solid hands-on approach to learning how to describe natural language semantics.

This book presents a broad range of deep-learning applications related to vision, natural language processing, gene expression, arbitrary object recognition, driverless cars, semantic image segmentati

Getting to grips with artificial intelligence (AI) and the way it's changing the world of work is essential for HR professionals. From using natural language processing to ensure job adverts are free

This open access book provides new methodological and theoretical insights into temporal reference and its linguistic expression, from a cross-linguistic experimental corpus pragmatics approach. Verbal tenses, in general, and more specifically the categories of tense, grammatical and lexical aspect are treated as cohesion ties contributing to the temporal coherence of a discourse, as well as to the cognitive temporal coherence of the mental representations built in the language comprehension process. As such, it investigates the phenomenon of temporal reference at the interface between corpus linguistics, theoretical linguistics and pragmatics, experimental pragmatics, psycholinguistics, natural language processing and machine translation.

This open access book describes the results of natural language processing and machine learning methods applied to clinical text from electronic patient records. It is divided into twelve chapters. Ch

本書重點介紹了神經網絡模型在自然語言處理中的應用。首先介紹有監督的機器學習和前饋神經網絡的基本知識，如何將機器學習方法應用在自然語言處理中，以及詞向量表示（而不是符號表示）的應用。然後介紹更多專門的神經網絡結構，包括一維卷積神經網絡、循環神經網絡、條件生成模型和基於注意力的模型。後，討論樹形網絡、結構化預測以及多任務學習的前景。

Text analytics is a field that lies on the interface of information retrieval,machine learning, and natural language processing, and this textbook carefully covers a coherently organized framework dra

Build smart applications using cutting-edge technologies such as rules engines, code automation frameworks, and natural language processing (NLP). This book provides step-by-step instructions on how t

TensorFlow is currently the leading open-source software for deep learning, used by a rapidly growing number of practitioners working on computer vision, Natural Language Processing (NLP), speech reco

Tackle a variety of tasks in natural language processing by learning how to use the R language and tidy data principles. This practical guide provides examples and resources to help you get up to spee

New edition of the successful communication-focused course that builds young adult and adult learners‘ confidence to use English and communicate in everyday situations.Breakthrough Plus 2nd edition contains up-to-date content, a fresh design, and a digital version of the Student's Book. This new edition is a truly blended, flexible, content-rich course, which covers high-interest themes in a thorough but accessible way.● NEW: Student's Resource Center, and page-faithful Digital Student's Book with integrated audio and video, extra practice, and over 150 interactive activities with score reports● NEW: Additional video material, including conversations, interactive real life exchanges, and interviews with viewing skills tasks● NEW: Presentation skills with practical guidance on how to present successfully in English● Broad, international, cross-cultural themes● Authentic natural language presented and practiced through clear, contextualized, and achievable tasks● Genuine flexibility and fo

This book presents state-of-the-art applications of digital watermarking in audio, speech, image, video, 3D graph, text, software, XML, database and natural language processing. It also presents new a

Social media is an invaluable source of time-critical information during a crisis. However, emergency response and humanitarian relief organizations that would like to use this information struggle with an avalanche of social media messages that exceeds the human capacity to process. Emergency managers, decision makers, and affected communities can make sense of social media through a combination of machine computation and human compassion - expressed by thousands of digital volunteers who publish, process, and summarize potentially life-saving information. This book brings together computational methods from many disciplines: natural language processing, semantic technologies, data mining, machine learning, network analysis, human-computer interaction, and information visualization, focusing on methods that are commonly used for processing social media messages under time-critical constraints, and offering more than 500 references to in-depth information.

Essentials of Programming in Mathematica® provides an introduction suitable for readers with little or no background in the language as well as for those with some experience using programs such as C, Java, or Perl. The author, an established authority on Mathematica® programming, has written an example-driven text that covers the language from first principles, as well as including material from natural language processing, bioinformatics, graphs and networks, signal analysis, geometry, computer science, and many other applied areas. The book is appropriate for self-study or as a text for a course in programming in computational science. Readers will benefit from the author's tips, which provide insight and suggestions on small and large points. He also provides more than 350 exercises from novice through to advanced level with all of the solutions available online.

This edited volume provides an overview of the latest advancements in adaptive training technology. Intelligent tutoring has been deployed for well-defined and relatively static educational domains such as algebra and geometry. However, this adaptive approach to computer-based training has yet to come into wider usage for domains that are less well defined or where student-system interactions are less structured, such as during scenario-based simulation and immersive serious games. In order to address how to expand the reach of adaptive training technology to these domains, leading experts in the field present their work in areas such as student modeling, pedagogical strategy, knowledge assessment, natural language processing and virtual human agents. Several approaches to designing adaptive technology are discussed for both traditional educational settings and professional training domains. This book will appeal to anyone concerned with educational and training technology at a profess

The book is intended for lectures on string processes and pattern matching in Master's courses of computer science and software engineering curricula. The details of algorithms are given with correctness proofs and complexity analysis, which make them ready to implement. Algorithms are described in a C-like language. The book is also a reference for students in computational linguistics or computational biology. It presents examples of questions related to the automatic processing of natural language, to the analysis of molecular sequences, and to the management of textual databases.

Selected from presentations at the March 2011 conference Meaning, Context, and Cognition, in Lodz, Poland, 13 papers explore cognitive aspects of processing natural language data in the interface of s

In the past few decades the use of increasingly large text corpora has grown rapidly in language and linguistics research. This was enabled by remarkable strides in natural language processing (NLP) t

The community responsible for developing lexicons for Natural Language Processing (NLP) and Machine Readable Dictionaries (MRDs) started their ISO standardization activities in 2003. These activities

Statistical models recently developed in several research communities (natural language processing, information retrieval, machine learning) for textual information access pertain to several applicati

This edited volume provides an overview of the latest advancements in adaptive training technology. Intelligent tutoring has been deployed for well-defined and relatively static educational domains such as algebra and geometry. However, this adaptive approach to computer-based training has yet to come into wider usage for domains that are less well defined or where student-system interactions are less structured, such as during scenario-based simulation and immersive serious games. In order to address how to expand the reach of adaptive training technology to these domains, leading experts in the field present their work in areas such as student modeling, pedagogical strategy, knowledge assessment, natural language processing and virtual human agents. Several approaches to designing adaptive technology are discussed for both traditional educational settings and professional training domains. This book will appeal to anyone concerned with educational and training technology at a profess

Behavioral scientists – including those in psychology, infant and child development, education, animal behavior, marketing and usability studies – use many methods to measure behavior. Systematic observation is used to study relatively natural, spontaneous behavior as it unfolds sequentially in time. This book emphasizes digital means to record and code such behavior; while observational methods do not require them, they work better with them. Key topics include devising coding schemes, training observers and assessing reliability, as well as recording, representing and analyzing observational data. In clear and straightforward language, this book provides a thorough grounding in observational methods along with considerable practical advice. It describes standard conventions for sequential data and details how to perform sequential analysis with a computer program developed by the authors. The book is rich with examples of coding schemes and different approaches to sequential analysis

Behavioral scientists – including those in psychology, infant and child development, education, animal behavior, marketing and usability studies – use many methods to measure behavior. Systematic observation is used to study relatively natural, spontaneous behavior as it unfolds sequentially in time. This book emphasizes digital means to record and code such behavior; while observational methods do not require them, they work better with them. Key topics include devising coding schemes, training observers and assessing reliability, as well as recording, representing and analyzing observational data. In clear and straightforward language, this book provides a thorough grounding in observational methods along with considerable practical advice. It describes standard conventions for sequential data and details how to perform sequential analysis with a computer program developed by the authors. The book is rich with examples of coding schemes and different approaches to sequential analysis

This book describes and explains the methods by which three related ores and recyclables are made into high purity metals and chemicals, for materials processing. It focuses on present day processes and future developments rather than historical processes. Nickel, cobalt and platinum group metals are key elements for materials processing. They occur together in one book because they (i) map together on the periodic table (ii) occur together in many ores and (iii) are natural partners for further materials processing and materials manufacturing. They all are, for example, important catalysts - with platinum group metals being especially important for reducing car and truck emissions. Stainless steels and CoNiFe airplane engine super alloys are examples of practical usage. The product emphasises a sequential, building-block approach to the subject gained through the author's previous writings (particularly Extractive Metallurgy of Copper in four editions) and extensive experience. Du

Computational semantics is the art and science of computing meaning in natural language. The meaning of a sentence is derived from the meanings of the individual words in it, and this process can be made so precise that it can be implemented on a computer. Designed for students of linguistics, computer science, logic and philosophy, this comprehensive text shows how to compute meaning using the functional programming language Haskell. It deals with both denotational meaning (where meaning comes from knowing the conditions of truth in situations), and operational meaning (where meaning is an instruction for performing cognitive action). Including a discussion of recent developments in logic, it will be invaluable to linguistics students wanting to apply logic to their studies, logic students wishing to learn how their subject can be applied to linguistics, and functional programmers interested in natural language processing as a new application area.

Computational semantics is the art and science of computing meaning in natural language. The meaning of a sentence is derived from the meanings of the individual words in it, and this process can be made so precise that it can be implemented on a computer. Designed for students of linguistics, computer science, logic and philosophy, this comprehensive text shows how to compute meaning using the functional programming language Haskell. It deals with both denotational meaning (where meaning comes from knowing the conditions of truth in situations), and operational meaning (where meaning is an instruction for performing cognitive action). Including a discussion of recent developments in logic, it will be invaluable to linguistics students wanting to apply logic to their studies, logic students wishing to learn how their subject can be applied to linguistics, and functional programmers interested in natural language processing as a new application area.

Yorick Wilks is a central figure in the fields of Natural Language Processing and Artificial Intelligence. This set consists of a volume of selected papers and a volume with contributions from his pee