This book is a collection of papers by leading researchers in computational semantics. It presents a state-of-the-art overview of recent and current research in computational semantics, including descriptions of new methods for constructing and improving resources for semantic computation, such as WordNet, VerbNet, and semantically annotated corpora. It also presents new statistical methods in semantic computation, such as the application of distributional semantics in the compositional calculation of sentence meanings. Computing the meaning of sentences, texts, and spoken or texted dialogue is the ultimate challenge in natural language processing, and the key to a wide range of exciting applications. The breadth and depth of coverage of this book makes it suitable as a reference and overview of the state of the field for researchers in Computational Linguistics, Semantics, Computer Science, Cognitive Science, and Artificial Intelligence. "

This book describes effective methods for automatically analyzing a sentence, based on the syntactic and semantic characteristics of the elements that form it. To tackle ambiguities, the authors use selectional preferences (SP), which measure how well two words fit together semantically in a sentence. Today, many disciplines require automatic text analysis based on the syntactic and semantic characteristics of language and as such several techniques for parsing sentences have been proposed. Which is better? In this book the authors begin with simple heuristics before moving on to more complex methods that identify nouns and verbs and then aggregate modifiers, and lastly discuss methods that can handle complex subordinate and relative clauses. During this process, several ambiguities arise. SP are commonly determined on the basis of the association between a pair of words. However, in many cases, SP depend on more words. For example, something (such as grass) may be edible, depending on who is eating it (a cow?). Moreover, things such as popcorn are usually eaten at the movies, and not in a restaurant. The authors deal with these phenomena from different points of view.

Language ability is a unique human trait, and it is indispensable throughout the human life cycle. Blockchain on the other hand, is an innovation that will transform production relationships, change collaboration models and distribution of benefits between people. Language and blockchain seem to have no intersection, yet they are bewilderingly similar in certain ways.When Language Meets Blockchain leads us into an exploratory journey to discover the possibilities of integrating blockchain technology with the language services industry. The author discusses how blockchain technology enables translators to realise their full potential and describes how the role of language can be elevated from a general tool to a driving force through a new concept called Cross-Linguistic Capability. This is a concept that will have very intriguing and beneficial implications for global economic activities.It is demonstrated that language is more than just a tool, it is also a resource and a form of capability. This presents opportunities for cross-linguistic and cross-cultural communications in the era of blockchain, to enable the convergence of linguistic capability with blockchain technology and artificial intelligence. The book's perspective on how the language services industry could adapt to times to embrace blockchain technology for industrial transformation, is both forwarding-looking and value enhancing.

The Routledge Handbook of Corpus Linguistics 2e provides an updated overview of a dynamic and rapidly growing area with a widely applied methodology. Over a decade on from the first edition of the Handbook, this collection of 47 chapters from experts in key areas offers a comprehensive introduction to both the development and use of corpora as well as their ever-evolving applications to other areas, such as digital humanities, sociolinguistics, stylistics, translation studies, materials design, language teaching and teacher development, media discourse, discourse analysis, forensic linguistics, second language acquisition and testing. The new edition updates all core chapters and includes new chapters on corpus linguistics and statistics, digital humanities, translation, phonetics and phonology, second language acquisition, social media and theoretical perspectives. Chapters provide annotated further reading lists and step-by-step guides as well as detailed overviews across a wide range of themes. The Handbook also includes a wealth of case studies that draw on some of the many new corpora and corpus tools that have emerged in the last decade. Organised across four themes, moving from the basic start-up topics such as corpus building and design to analysis, application and reflection, this second edition remains a crucial point of reference for advanced undergraduates, postgraduates and scholars in applied linguistics.

This book is about the role of knowledge in information systems. Knowledge is usually articulated and exchanged through human language(s). In this sense, language can be seen as the most natural vehicle to convey our concepts, whose meanings are usually intermingled, grouped and organized according to shared criteria, from simple perceptions ( every tree has a stem ) and common sense ( unsupported objects fall ) to complex social conventions ( a tax is a fee charged by a government on a product, income, or activity ). But what is natural for a human being turns out to be extremely difficult for machines: machines need to be instilled with knowledge and suitably equipped with logical and statistical algorithms to reason over it. Computers can t represent the external world and communicate their representations as effectively as humans do: ontologies and NLP have been invented to face this problem: in particular, integrating ontologies with (possibly multi-lingual) computational lexical resources is an essential requirement to make human meanings understandable by machines. This book explores the advancements in this integration, from the most recent steps in building the necessary infrastructure, i.e. the Semantic Web, to the different knowledge contents that can be analyzed, encoded and transferred (multimedia, emotions, events, etc.) through it. The work aims at presenting the progress in the field of integrating ontologies and lexicons: together, they constitute the essential technology for adequately represent, elicit and exchange knowledge contents in information systems, web services, text processing and several other domains of application.

The application of deep learning methods to problems in natural language processing has generated significant progress across a wide range of natural language processing tasks. For some of these applications, deep learning models now approach or surpass human performance. While the success of this approach has transformed the engineering methods of machine learning in artificial intelligence, the significance of these achievements for the modelling of human learning and representation remains unclear. Deep Learning and Linguistic Representation looks at the application of a variety of deep learning systems to several cognitively interesting NLP tasks. It also considers the extent to which this work illuminates our understanding of the way in which humans acquire and represent linguistic knowledge. Key Features: combines an introduction to deep learning in AI and NLP with current research on Deep Neural Networks in computational linguistics. is self-contained and suitable for teaching in computer science, AI, and cognitive science courses; it does not assume extensive technical training in these areas. provides a compact guide to work on state of the art systems that are producing a revolution across a range of difficult natural language tasks.

Posthumanism and Deconstructing Arguments: Corpora and Digitally-driven Critical Analysis presents a new and practical approach in Critical Discourse Studies. Providing a data-driven and ethically-based method for the examination of arguments in the public sphere, this ground-breaking book: Highlights how the reader can evaluate arguments from points of view other than their own; Demonstrates how digital tools can be used to generate 'ethical subjectivities' from large numbers of dissenting voices on the world-wide-web; Draws on ideas from posthumanist philosophy as well as from Jacques Derrida, Gilles Deleuze and Felix Guattari for theorising these subjectivities; Showcases a critical deconstructive approach, using different corpus linguistic programs such as AntConc, WMatrix and Sketchengine. Posthumanism and Deconstructing Arguments is essential reading for lecturers and researchers with an interest in critical discourse studies, critical thinking, corpus linguistics and digital humanities.

This book focuses on the next generation optical networks as well as mobile communication technologies. The reader will find chapters on Cognitive Optical Network, 5G Cognitive Wireless, LTE, Data Analysis and Natural Language Processing. It also presents a comprehensive view of the enhancements and requirements foreseen for Machine Type Communication. Moreover, some data analysis techniques and Brazilian Portuguese natural language processing technologies are also described here.

In today's unsafe and increasingly wired world cryptology plays a vital role in protecting communication channels, databases, and software from unwanted intruders. This revised and extended third edition of the classic reference work on cryptology now contains many new technical and biographical details. The first part treats secret codes and their uses - cryptography. The second part deals with the process of covertly decrypting a secret code - cryptanalysis, where particular advice on assessing methods is given. The book presupposes only elementary mathematical knowledge. Spiced with a wealth of exciting, amusing, and sometimes personal stories from the history of cryptology, it will also interest general readers.

The application of deep learning methods to problems in natural language processing has generated significant progress across a wide range of natural language processing tasks. For some of these applications, deep learning models now approach or surpass human performance. While the success of this approach has transformed the engineering methods of machine learning in artificial intelligence, the significance of these achievements for the modelling of human learning and representation remains unclear. Deep Learning and Linguistic Representation looks at the application of a variety of deep learning systems to several cognitively interesting NLP tasks. It also considers the extent to which this work illuminates our understanding of the way in which humans acquire and represent linguistic knowledge. Key Features: combines an introduction to deep learning in AI and NLP with current research on Deep Neural Networks in computational linguistics. is self-contained and suitable for teaching in computer science, AI, and cognitive science courses; it does not assume extensive technical training in these areas. provides a compact guide to work on state of the art systems that are producing a revolution across a range of difficult natural language tasks.

Universal codes efficiently compress sequences generated by stationary and ergodic sources with unknown statistics, and they were originally designed for lossless data compression. In the meantime, it was realized that they can be used for solving important problems of prediction and statistical analysis of time series, and this book describes recent results in this area. The first chapter introduces and describes the application of universal codes to prediction and the statistical analysis of time series; the second chapter describes applications of selected statistical methods to cryptography, including attacks on block ciphers; and the third chapter describes a homogeneity test used to determine authorship of literary texts. The book will be useful for researchers and advanced students in information theory, mathematical statistics, time-series analysis, and cryptography. It is assumed that the reader has some grounding in statistics and in information theory.

This is the first volume that brings together research and practice from academic and industry settings and a combination of human and machine translation evaluation. Its comprehensive collection of papers by leading experts in human and machine translation quality and evaluation who situate current developments and chart future trends fills a clear gap in the literature. This is critical to the successful integration of translation technologies in the industry today, where the lines between human and machine are becoming increasingly blurred by technology: this affects the whole translation landscape, from students and trainers to project managers and professionals, including in-house and freelance translators, as well as, of course, translation scholars and researchers. The editors have broad experience in translation quality evaluation research, including investigations into professional practice with qualitative and quantitative studies, and the contributors are leading experts in their respective fields, providing a unique set of complementary perspectives on human and machine translation quality and evaluation, combining theoretical and applied approaches.

Mathematical Linguistics introduces the mathematical foundations of linguistics to computer scientists, engineers, and mathematicians interested in natural language processing. The book presents linguistics as a cumulative body of knowledge from the ground up: no prior knowledge of linguistics is assumed. Previous textbooks in this area concentrate on syntax and semantics - this comprehensive volume covers an extremely rich array of topics also including phonology and morphology, probabilistic approaches, complexity, learnability, and the analysis of speech and handwriting. As the first textbook of its kind, this book is useful for those in information science (information retrieval and extraction, search engines) and in natural language technologies (speech recognition, optical character recognition, HCI). Exercises suitable for the advanced reader are included, as well as suggestions for further reading and an extensive bibliography.

Handbook of Artificial Intelligence in Biomedical Engineering focuses on recent AI technologies and applications that provide some very promising solutions and enhanced technology in the biomedical field. Recent advancements in computational techniques, such as machine learning, Internet of Things (IoT), and big data, accelerate the deployment of biomedical devices in various healthcare applications. This volume explores how artificial intelligence (AI) can be applied to these expert systems by mimicking the human expert's knowledge in order to predict and monitor the health status in real time. The accuracy of the AI systems is drastically increasing by using machine learning, digitized medical data acquisition, wireless medical data communication, and computing infrastructure AI approaches, helping to solve complex issues in the biomedical industry and playing a vital role in future healthcare applications. The volume takes a multidisciplinary perspective of employing these new applications in biomedical engineering, exploring the combination of engineering principles with biological knowledge that contributes to the development of revolutionary and life-saving concepts.

This book provides a wide variety of algorithms and models to integrate linguistic knowledge into Statistical Machine Translation (SMT). It helps advance conventional SMT to linguistically motivated SMT by enhancing the following three essential components: translation, reordering and bracketing models. It also serves the purpose of promoting the in-depth study of the impacts of linguistic knowledge on machine translation. Finally it provides a systematic introduction of Bracketing Transduction Grammar (BTG) based SMT, one of the state-of-the-art SMT formalisms, as well as a case study of linguistically motivated SMT on a BTG-based platform.

The volume discusses a multitude of ways in which CALL can serve to develop and support broadly conceived issues-of background in language education. The individual chapters explore a number of areas in which CALL techniques and tools enhance language instruction. The issues reported on comprise working with mature language learners, developing civic education, ICT affordances for ESP, professional training for translators, interpreters and crowdsourcing opportunities. Other contributions center around CALL-related resources, CAPT metacompetence and blended-learning paradigms as well as exploring cultural and linguistic issues in online exchanges.

This book applies linguistic analysis to the poetry of Emeritus Professor Edwin Thumboo, a Singaporean poet and leading figure in Commonwealth literature. The work explores how the poet combines grammar and metaphor to create meaning, making the reader aware of the linguistic resources developed by Thumboo as the basis for his unique technique. The author approaches the poems from a functional linguistic perspective, investigating the multiple layers of meaning and metaphor that go into producing these highly textured, grammatically intricate verbal works of art. The approach is based on the Systemic Functional Theory, which aids the study of how the poet uses language (grammar) to craft his text in a playful way that reflects a love of the language. The multilingual and multicultural experiences of the poet are considered to have contributed to his uniquely creative use of language. This work demonstrates how the Systemic Functional Theory, with its emphasis on exploring the semogenic (meaning-making) power of language, provides the perspective we need to better understand poets' works as intentional acts of meaning. Readers will discover how the works of Edwin Thumboo illustrate well a point made by Barthes, who noted that "Bits of code, formulae, rhythmic models, fragments of social languages, etc. pass into the text and are redistributed within it, for there is always language before and around the text." With a focus on meaning, this functional analysis of poetry offers an insightful look at the linguistic basis of Edwin Thumboo's poetic technique. The work will appeal to scholars with an interest in linguistic analysis and poetry from the Commonwealth and new literature, and it can also be used to support courses on literary stylistics or text linguistics.

More than ever, professional English is now cruising towards an enormous challenge in the European university context due to the extremely significant moment we are living in the European Higher Education Area (EHEA). The European convergence process is demanding immediate reflections, serious analyses, and profound reforms in specialized language teaching that lead to reach Bologna standards by 2010. This book aims to present an overview of professional English in the current academic landscape in Europe. It intends to shed light on a range of issues, both theoretical and practical, related to ESP, focusing on discourse analysis, corpus analysis, information and communication technologies, methodological approaches, curriculum design, and empirical research into language learning in broad terms. Because teachers need to be researchers and inquirers, this overview thus makes a contribution to the professional English field with the purpose of highlighting several important questions in the entire ESP academic mainstream. Scholars from different European universities explore specialized languages and document ESP teaching methodologies at university levels from a multidimensional perspective.

This book advances the growing area of language policy and planning (LPP) by examining the epistemological and theoretical foundations that engendered and sustain the field, drawing on insights and approaches from anthropology, linguistics, economics, political science, and education to create an accessible and inter-disciplinary overview of LPP as a coherent discipline. Throughout the book, the authors address LPP from different perspectives, exploring the interface between planning in theory and its practical problems in implementation. This volume will be of interest to students and scholars with an interest in LPP in particular, and educational, social, and public policy more broadly.

This book presents a comprehensive overview of semi-supervised approaches to dependency parsing. Having become increasingly popular in recent years, one of the main reasons for their success is that they can make use of large unlabeled data together with relatively small labeled data and have shown their advantages in the context of dependency parsing for many languages. Various semi-supervised dependency parsing approaches have been proposed in recent works which utilize different types of information gleaned from unlabeled data. The book offers readers a comprehensive introduction to these approaches, making it ideally suited as a textbook for advanced undergraduate and graduate students and researchers in the fields of syntactic parsing and natural language processing.

This book unites a range of approaches to the collection and digitization of diverse language corpora. Its specific focus is on best practices identified in the exploitation of these resources in landmark impact initiatives across different parts of the globe. The development of increasingly accessible digital corpora has coincided with improvements in the standards governing the collection, encoding and archiving of 'Big Data'. Less attention has been paid to the importance of developing standards for enriching and preserving other types of corpus data, such as that which captures the nuances of regional dialects, for example. This book takes these best practices another step forward by addressing innovative methods for enhancing and exploiting specialized corpora so that they become accessible to wider audiences beyond the academy.

Corpus linguistics is one of the most exciting approaches tostudies in applied linguistics today. From its quantitative beginnings it hasgrown to become an essential aspect of research methodology in a range offields, often combining with text analysis, CDA, pragmatics and organizationalstudies to reveal important new insights about how language works. This important new book of specially commissioned chapters byacademics from across the applied linguistics spectrum demonstrates the range andrigour of corpus research in applied linguistics. The volume captures some ofthe most stimulating and significant developments in the field, includingchapters on language teaching, institutional and professional discourse, English as an International Language, translation, forensics and media studies. As a result it goes beyond traditional, limited presentations of corpuswork and shows how corpora inform a diverse and growing number of appliedlinguistic domains.

The next big area within the information and communication technology field is Artificial Intelligence (AI). The industry is moving to automate networks, cloud-based systems (e.g., Salesforce), databases (e.g., Oracle), AWS machine learning (e.g., Amazon Lex), and creating infrastructure that has the ability to adapt in real-time to changes and learn what to anticipate in the future. It is an area of technology that is coming faster and penetrating more areas of business than any other in our history. AI will be used from the C-suite to the distribution warehouse floor. Replete with case studies, this book provides a working knowledge of AI's current and future capabilities and the impact it will have on every business. It covers everything from healthcare to warehousing, banking, finance and education. It is essential reading for anyone involved in industry.

This book builds on decades of research and provides contemporary theoretical foundations for practical applications to intelligent technologies and advances in artificial intelligence (AI). Reflecting the growing realization that computational models of human reasoning and interactions can be improved by integrating heterogeneous information resources and AI techniques, its ultimate goal is to promote integrated computational approaches to intelligent computerized systems. The book covers a range of interrelated topics, in particular, computational reasoning, language, syntax, semantics, memory, and context information. The respective chapters use and develop logically oriented methods and techniques, and the topics selected are from those areas of logic that contribute to AI and provide its mathematical foundations. The intended readership includes researchers working in the areas of traditional logical foundations, and on new approaches to intelligent computational systems.

The "Yearbook of Corpus Linguistics and Pragmatics" "2013" discusses current methodological debates on the synergy of Corpus Linguistics and Pragmatics research. The volume presents insightful pragmatic analyses of corpora in new technological domains and devotes some chapters to the pragmatic description of spoken corpora from various theoretical traditions.

The "Yearbook of Corpus Linguistics and Pragmatics" series will give readers insight into how pragmatics can be used to explain real corpus data, and, in addition, how corpora can explain pragmatic intuitions, and from there, develop and refine theory. Corpus Linguistics can offer a meticulous methodology based on mathematics and statistics, while Pragmatics is characterized by its efforts to interpret intended meaning in real language. This yearbook offers a platform to scholars who combine both research methodologies to present rigorous and interdisciplinary findings about language in real use.