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computer science and linguistics: Programming Linguistics David Hillel Gelernter, Suresh Jagannathan, 1990 Programming Linguistics examines a wide range of programming language designs, from Fortran to the newest research languages, to discover their common patterns, relationships, and antecedents. In studying the evolution of programming languages, the authors are also studying a series of answers to the central (and still unanswered) questions of what programs are and how they should be built. Programming Linguistics approaches language design as an attempt to define the nature of programming and the shape and structure of programs, rather than as the attempt to solve a series of narrow, disjoint technical problems. It emphasizes the structural-engineering rather than mathematical approach to programming, the importance of aesthetics and elegance in the success of language design, and provides an integrated treatment of concurrency and parallelism. Its readable and informal but rigorous coverage of the gamut of programming language designs is based on a simple and general programming model called the Ideal Software Machine. There are helpful exercises throughout. David Gelernter is an Associate Professor in the Department of Computer Science at Yale University. Suresh Jagannathan is an Associate Research Scientist at Yale. |
computer science and linguistics: Linguistics for the Age of AI Marjorie Mcshane, Sergei Nirenburg, 2021-03-02 A human-inspired, linguistically sophisticated model of language understanding for intelligent agent systems. One of the original goals of artificial intelligence research was to endow intelligent agents with human-level natural language capabilities. Recent AI research, however, has focused on applying statistical and machine learning approaches to big data rather than attempting to model what people do and how they do it. In this book, Marjorie McShane and Sergei Nirenburg return to the original goal of recreating human-level intelligence in a machine. They present a human-inspired, linguistically sophisticated model of language understanding for intelligent agent systems that emphasizes meaning--the deep, context-sensitive meaning that a person derives from spoken or written language. |
computer science and linguistics: Computational Linguistics and Intelligent Text Processing Alexander Gelbukh, 2009-02-17 th CICLing 2009 markedthe 10 anniversary of the Annual Conference on Intel- gent Text Processing and Computational Linguistics. The CICLing conferences provide a wide-scope forum for the discussion of the art and craft of natural language processing research as well as the best practices in its applications. This volume contains ?ve invited papers and the regular papers accepted for oral presentation at the conference. The papers accepted for poster presentation were published in a special issue of another journal (see the website for more information). Since 2001, the proceedings of CICLing conferences have been published in Springer’s Lecture Notes in Computer Science series, as volumes 2004, 2276, 2588, 2945, 3406, 3878, 4394, and 4919. This volume has been structured into 12 sections: – Trends and Opportunities – Linguistic Knowledge Representation Formalisms – Corpus Analysis and Lexical Resources – Extraction of Lexical Knowledge – Morphology and Parsing – Semantics – Word Sense Disambiguation – Machine Translation and Multilinguism – Information Extraction and Text Mining – Information Retrieval and Text Comparison – Text Summarization – Applications to the Humanities A total of 167 papers by 392 authors from 40 countries were submitted for evaluation by the International Program Committee, see Tables 1 and 2. This volume contains revised versions of 44 papers, by 120 authors, selected for oral presentation; the acceptance rate was 26. 3%. |
computer science and linguistics: Computational Linguistics Adam Przepiórkowski, Maciej Piasecki, Krzysztof Jassem, Piotr Fuglewicz, 2012-11-06 The ever-growing popularity of Google over the recent decade has required a specific method of man-machine communication: human query should be short, whereas the machine answer may take a form of a wide range of documents. This type of communication has triggered a rapid development in the domain of Information Extraction, aimed at providing the asker with a more precise information. The recent success of intelligent personal assistants supporting users in searching or even extracting information and answers from large collections of electronic documents signals the onset of a new era in man-machine communication – we shall soon explain to our small devices what we need to know and expect valuable answers quickly and automatically delivered. The progress of man-machine communication is accompanied by growth in the significance of applied Computational Linguistics – we need machines to understand much more from the language we speak naturally than it is the case of up-to-date search systems. Moreover, we need machine support in crossing language barriers that is necessary more and more often when facing the global character of the Web. This books reports on the latest developments in the field. It contains 15 chapters written by researchers who aim at making linguistic theories work – for the better understanding between the man and the machine. |
computer science and linguistics: Semisupervised Learning for Computational Linguistics Steven Abney, 2007-09-17 The rapid advancement in the theoretical understanding of statistical and machine learning methods for semisupervised learning has made it difficult for nonspecialists to keep up to date in the field. Providing a broad, accessible treatment of the theory as well as linguistic applications, Semisupervised Learning for Computational Linguistics offer |
computer science and linguistics: The Oxford Handbook of Computational Linguistics Ruslan Mitkov, 2004 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. |
computer science and linguistics: Linguistic Fundamentals for Natural Language Processing Emily M. Bender, 2013-06-01 Many NLP tasks have at their core a subtask of extracting the dependencies—who did what to whom—from natural language sentences. This task can be understood as the inverse of the problem solved in different ways by diverse human languages, namely, how to indicate the relationship between different parts of a sentence. Understanding how languages solve the problem can be extremely useful in both feature design and error analysis in the application of machine learning to NLP. Likewise, understanding cross-linguistic variation can be important for the design of MT systems and other multilingual applications. The purpose of this book is to present in a succinct and accessible fashion information about the morphological and syntactic structure of human languages that can be useful in creating more linguistically sophisticated, more language-independent, and thus more successful NLP systems. Table of Contents: Acknowledgments / Introduction/motivation / Morphology: Introduction / Morphophonology / Morphosyntax / Syntax: Introduction / Parts of speech / Heads, arguments, and adjuncts / Argument types and grammatical functions / Mismatches between syntactic position and semantic roles / Resources / Bibliography / Author's Biography / General Index / Index of Languages |
computer science and linguistics: Computational Linguistics Ralph Grishman, 1986-11-06 A highly respected introduction to the computer analysis of language. Copyright © Libri GmbH. All rights reserved. |
computer science and linguistics: Foundations of Computational Linguistics Roland Hausser, 2013-03-09 The central task of future-oriented computational linguistics is the development of cognitive machines which humans can freely speak to in their natural language. This will involve the development of a functional theory of language, an objective method of verification, and a wide range of practical applications. Natural communication requires not only verbal processing, but also non-verbal perception and action. Therefore, the content of this book is organized as a theory of language for the construction of talking robots with a focus on the mechanics of natural language communication in both the listener and the speaker. |
computer science and linguistics: The Handbook of Computational Linguistics and Natural Language Processing Alexander Clark, Chris Fox, Shalom Lappin, 2013-04-24 This comprehensive reference work provides an overview of the concepts, methodologies, and applications in computational linguistics and natural language processing (NLP). Features contributions by the top researchers in the field, reflecting the work that is driving the discipline forward Includes an introduction to the major theoretical issues in these fields, as well as the central engineering applications that the work has produced Presents the major developments in an accessible way, explaining the close connection between scientific understanding of the computational properties of natural language and the creation of effective language technologies Serves as an invaluable state-of-the-art reference source for computational linguists and software engineers developing NLP applications in industrial research and development labs of software companies |
computer science and linguistics: Human Language Technologies as a Challenge for Computer Science and Linguistics - 2023 Zygmunt Vetulani, Patrick Paroubek, Wydawnictwo Naukowe Uniwersytetu im. Adama Mickiewicza (Poznań), 2023 |
computer science and linguistics: Mathematical Methods in Linguistics Barbara B.H. Partee, A.G. ter Meulen, R. Wall, 1990-04-30 Elementary set theory accustoms the students to mathematical abstraction, includes the standard constructions of relations, functions, and orderings, and leads to a discussion of the various orders of infinity. The material on logic covers not only the standard statement logic and first-order predicate logic but includes an introduction to formal systems, axiomatization, and model theory. The section on algebra is presented with an emphasis on lattices as well as Boolean and Heyting algebras. Background for recent research in natural language semantics includes sections on lambda-abstraction and generalized quantifiers. Chapters on automata theory and formal languages contain a discussion of languages between context-free and context-sensitive and form the background for much current work in syntactic theory and computational linguistics. The many exercises not only reinforce basic skills but offer an entry to linguistic applications of mathematical concepts. For upper-level undergraduate students and graduate students in theoretical linguistics, computer-science students with interests in computational linguistics, logic programming and artificial intelligence, mathematicians and logicians with interests in linguistics and the semantics of natural language. |
computer science and linguistics: Natural Language Processing and Computational Linguistics Mohamed Zakaria Kurdi, 2016-08-22 Natural language processing (NLP) is a scientific discipline which is found at the interface of computer science, artificial intelligence and cognitive psychology. Providing an overview of international work in this interdisciplinary field, this book gives the reader a panoramic view of both early and current research in NLP. Carefully chosen multilingual examples present the state of the art of a mature field which is in a constant state of evolution. In four chapters, this book presents the fundamental concepts of phonetics and phonology and the two most important applications in the field of speech processing: recognition and synthesis. Also presented are the fundamental concepts of corpus linguistics and the basic concepts of morphology and its NLP applications such as stemming and part of speech tagging. The fundamental notions and the most important syntactic theories are presented, as well as the different approaches to syntactic parsing with reference to cognitive models, algorithms and computer applications. |
computer science and linguistics: Puzzles in Logic, Languages and Computation Dragomir Radev, 2013-02-11 This is the second volume of a unique collection that brings together the best English-language problems created for students competing in the Computational Linguistics Olympiad. These problems are representative of the diverse areas presented in the competition and designed with three principles in mind: · To challenge the student analytically, without requiring any explicit knowledge or experience in linguistics or computer science; · To expose the student to the different kinds of reasoning required when encountering a new phenomenon in a language, both as a theoretical topic and as an applied problem; · To foster the natural curiosity students have about the workings of their own language, as well as to introduce them to the beauty and structure of other languages; · To learn about the models and techniques used by computers to understand human language. Aside from being a fun intellectual challenge, the Olympiad mimics the skills used by researchers and scholars in the field of computational linguistics. In an increasingly global economy where businesses operate across borders and languages, having a strong pool of computational linguists is a competitive advantage, and an important component to both security and growth in the 21st century. This collection of problems is a wonderful general introduction to the field of linguistics through the analytic problem solving technique. A fantastic collection of problems for anyone who is curious about how human language works! These books take serious scientific questions and present them in a fun, accessible way. Readers exercise their logical thinking capabilities while learning about a wide range of human languages, linguistic phenomena, and computational models. - Kevin Knight, USC Information Sciences Institute |
computer science and linguistics: Python Programming for Linguistics and Digital Humanities Martin Weisser, 2024-01-31 Learn how to use Python for linguistics and digital humanities research, perfect for students working with Python for the first time Python programming is no longer only for computer science students; it is now an essential skill in linguistics, the digital humanities (DH), and social science programs that involve text analytics. Python Programming for Linguistics and Digital Humanities provides a comprehensive introduction to this widely used programming language, offering guidance on using Python to perform various processing and analysis techniques on text. Assuming no prior knowledge of programming, this student-friendly guide covers essential topics and concepts such as installing Python, using the command line, working with strings, writing modular code, designing a simple graphical user interface (GUI), annotating language data in XML and TEI, creating basic visualizations, and more. This invaluable text explains the basic tools students will need to perform their own research projects and tackle various data analysis problems. Throughout the book, hands-on exercises provide students with the opportunity to apply concepts to particular questions or projects in processing textual data and solving language-related issues. Each chapter concludes with a detailed discussion of the code applied, possible alternatives, and potential pitfalls or error messages. Teaches students how to use Python to tackle the types of problems they will encounter in linguistics and the digital humanities Features numerous practical examples of language analysis, gradually moving from simple concepts and programs to more complex projects Describes how to build a variety of data visualizations, such as frequency plots and word clouds Focuses on the text processing applications of Python, including creating word and frequency lists, recognizing linguistic patterns, and processing words for morphological analysis Includes access to a companion website with all Python programs produced in the chapter exercises and additional Python programming resources Python Programming for Linguistics and Digital Humanities: Applications for Text-Focused Fields is a must-have resource for students pursuing text-based research in the humanities, the social sciences, and all subfields of linguistics, particularly computational linguistics and corpus linguistics. |
computer science and linguistics: Language and Computers Markus Dickinson, Chris Brew, Detmar Meurers, 2012-08-20 Language and Computers introduces students to the fundamentals of how computers are used to represent, process, and organize textual and spoken information. Concepts are grounded in real-world examples familiar to students’ experiences of using language and computers in everyday life. A real-world introduction to the fundamentals of how computers process language, written specifically for the undergraduate audience, introducing key concepts from computational linguistics. Offers a comprehensive explanation of the problems computers face in handling natural language Covers a broad spectrum of language-related applications and issues, including major computer applications involving natural language and the social and ethical implications of these new developments The book focuses on real-world examples with which students can identify, using these to explore the technology and how it works Features “under-the-hood” sections that give greater detail on selected advanced topics, rendering the book appropriate for more advanced courses, or for independent study by the motivated reader. |
computer science and linguistics: Chinese Computational Linguistics Sheng Li, Maosong Sun, Yang Liu, Hua Wu, Liu Kang, Wanxiang Che, Shizhu He, Gaoqi Rao, 2021-08-07 This book constitutes the proceedings of the 20th China National Conference on Computational Linguistics, CCL 2021, held in Hohhot, China, in August 2021. The 31 full presented in this volume were carefully reviewed and selected from 90 submissions. The conference papers covers the following topics such as Machine Translation and Multilingual Information Processing, Minority Language Information Processing, Social Computing and Sentiment Analysis, Text Generation and Summarization, Information Retrieval, Dialogue and Question Answering, Linguistics and Cognitive Science, Language Resource and Evaluation, Knowledge Graph and Information Extraction, and NLP Applications. |
computer science and linguistics: Statistics for Corpus Linguistics Michael Oakes, 2019-08-06 This book in the Edinburgh Textbooks in Empirical Linguistics series is a comprehensive introduction to the statistics currently used in corpus linguistics. Statistical techniques and corpus applications - whether oriented towards linguistics or language engineering - often go hand in glove, and corpus linguists have used an increasingly wide variety of statistics, drawing on techniques developed in a great many fields. This is the first one-volume introduction to the subject. |
computer science and linguistics: Human Language Technology Challenges for Computer Science and Linguistics Zygmunt Vetulani, Joseph Mariani, 2014-07-25 This book constitutes the refereed proceedings of the 5th Language and Technology Conference: Challenges for Computer Science and Linguistics, LTC 2011, held in Poznan, Poland, in November 2011. The 44 revised and in many cases substantially extended papers presented in this volume were carefully reviewed and selected from 111 submissions. The focus of the papers is on the following topics: speech, parsing, computational semantics, text analysis, text annotation, language resources: general issues, language resources: ontologies and Wordnets and machine translation. |
computer science and linguistics: Python for Linguists Michael Hammond, 2020-05-07 An introduction to Python programming for linguists. Examples of code specifically designed for language analysis are featured throughout. |
computer science and linguistics: Computer-Mediated Communication for Linguistics and Literacy: Technology and Natural Language Education Bodomo, Adams B., 2009-07-31 This book investigates the way humans communicate through the medium of information technology gadgets, focusing on the linguistic, literacy and educational aspects of computer-mediated communication--Provided by publisher. |
computer science and linguistics: Where Mathematics, Computer Science, Linguistics and Biology Meet Carlos Martín-Vide, V. Mitrana, 2013-03-14 In the last years, it was observed an increasing interest of computer scientists in the structure of biological molecules and the way how they can be manipulated in vitro in order to define theoretical models of computation based on genetic engineering tools. Along the same lines, a parallel interest is growing regarding the process of evolution of living organisms. Much of the current data for genomes are expressed in the form of maps which are now becoming available and permit the study of the evolution of organisms at the scale of genome for the first time. On the other hand, there is an active trend nowadays throughout the field of computational biology toward abstracted, hierarchical views of biological sequences, which is very much in the spirit of computational linguistics. In the last decades, results and methods in the field of formal language theory that might be applied to the description of biological sequences were pointed out. |
computer science and linguistics: Human Language Technology. Challenges for Computer Science and Linguistics Zygmunt Vetulani, Hans Uszkoreit, Marek Kubis, 2016-07-29 This book constitutes the refereed proceedings of the 6th Language and Technology Conference: Challenges for Computer Science and Linguistics, LTC 2013, held in Poznań, Poland, in December 2013. The 31 revised and in many cases substantially extended papers presented in this volume were carefully reviewed and selected from 103 submissions.The papers selected to this volume belong to various fields of Human Language Technologies and illustrate a large thematic coverage of the LTC conferences. To make the presentation of the papers possibly transparent we have “structured” them into 9 chapters. These are: Speech Processing, Morphology, Parsing Related Issues, Computational Semantics, Digital Language Resources, Ontologies and Wordnets, Written Text and Document Processing, Information and Data Extraction, and Less-Resourced Languages. |
computer science and linguistics: Quantitative Corpus Linguistics with R Stefan Th. Gries, 2009-03-04 The first textbook of its kind, Quantitative Corpus Linguistics with R demonstrates how to use the open source programming language R for corpus linguistic analyses. Computational and corpus linguists doing corpus work will find that R provides an enormous range of functions that currently require several programs to achieve – searching and processing corpora, arranging and outputting the results of corpus searches, statistical evaluation, and graphing. |
computer science and linguistics: Human Language Technology. Challenges for Computer Science and Linguistics Zygmunt Vetulani, Patrick Paroubek, Marek Kubis, 2022-06-04 This book constitutes the refereed proceedings of the 9th Language and Technology Conference: Challenges for Computer Science and Linguistics, LTC 2019, held in Poznan, Poland, in May 2019. The 24 revised papers presented in this volume were carefully reviewed and selected from 67 submissions. The papers are categorized into the following topical sub-headings: Speech Processing; Language Resources and Tools; Computational Semantics; Emotions, Decisions and Opinions; Digital Humanities; Evaluation; and Legal Aspects. |
computer science and linguistics: Directions in Corpus Linguistics Jan Svartvik, 2011-06-01 TRENDS IN LINGUISTICS is a series of books that open new perspectives in our understanding of language. The series publishes state-of-the-art work on core areas of linguistics across theoretical frameworks, as well as studies that provide new insights by approaching language from an interdisciplinary perspective. TRENDS IN LINGUISTICS considers itself a forum for cutting-edge research based on solid empirical data on language in its various manifestations, including sign languages. It regards linguistic variation in its synchronic and diachronic dimensions as well as in its social contexts as important sources of insight for a better understanding of the design of linguistic systems and the ecology and evolution of language. TRENDS IN LINGUISTICS publishes monographs and outstanding dissertations as well as edited volumes, which provide the opportunity to address controversial topics from different empirical and theoretical viewpoints. High quality standards are ensured through anonymous reviewing. To discuss your book idea or submit a proposal, please contact Birgit Sievert. |
computer science and linguistics: Corpus Linguistics McEnery Tony McEnery, 2019-08-06 Corpus Linguistics has quickly established itself as the leading undergraduate course book in the subject. This second edition takes full account of the latest developments in the rapidly changing field, making this the most up-to-date and comprehensive textbook available. It gives a step-by-step introduction to what a corpus is, how corpora are constructed, and what can be done with them. Each chapter ends with a section of study questions that contain practical corpus-based exercises.* Designed for student use, with all technical terms explained in the text and referenced further in a Glossary* Examples are taken from existing corpora; detailed case study chapter included* Contains end-of-chapter summaries, study questions and suggestions for further reading* Updated reviews of new studies, areas that have recently come to prominence and new directions in corpus encoding and annotation standards* Detailed coverage of multilingual corpus construction and use* An in-depth historical review of computer-based corpora from the 1940s to the present day* Helpful appendices include answers to the study questions, up-to-date information on where corpora can be found, and the latest software for corpus research.e;[An] important addition to the fast growing literature in corpus linguistics... should be read by anyone interested in utilization of large-scale corpora in linguistic research.e; Studies in the Linguistic Sciences, on the first edition |
computer science and linguistics: Syntactic Structures Noam Chomsky, 2020-05-18 No detailed description available for Syntactic Structures. |
computer science and linguistics: Using R for Introductory Statistics John Verzani, 2018-10-03 The second edition of a bestselling textbook, Using R for Introductory Statistics guides students through the basics of R, helping them overcome the sometimes steep learning curve. The author does this by breaking the material down into small, task-oriented steps. The second edition maintains the features that made the first edition so popular, while updating data, examples, and changes to R in line with the current version. See What’s New in the Second Edition: Increased emphasis on more idiomatic R provides a grounding in the functionality of base R. Discussions of the use of RStudio helps new R users avoid as many pitfalls as possible. Use of knitr package makes code easier to read and therefore easier to reason about. Additional information on computer-intensive approaches motivates the traditional approach. Updated examples and data make the information current and topical. The book has an accompanying package, UsingR, available from CRAN, R’s repository of user-contributed packages. The package contains the data sets mentioned in the text (data(package=UsingR)), answers to selected problems (answers()), a few demonstrations (demo()), the errata (errata()), and sample code from the text. The topics of this text line up closely with traditional teaching progression; however, the book also highlights computer-intensive approaches to motivate the more traditional approach. The authors emphasize realistic data and examples and rely on visualization techniques to gather insight. They introduce statistics and R seamlessly, giving students the tools they need to use R and the information they need to navigate the sometimes complex world of statistical computing. |
computer science and linguistics: Speech & Language Processing Dan Jurafsky, 2000-09 |
computer science and linguistics: Handbook of Research on Engineering Innovations and Technology Management in Organizations Gaur, Loveleen, Solanki, Arun, Jain, Vishal, Khazanchi, Deepak, 2020-04-17 As technology weaves itself more tightly into everyday life, socio-economic development has become intricately tied to these ever-evolving innovations. Technology management is now an integral element of sound business practices, and this revolution has opened up many opportunities for global communication. However, such swift change warrants greater research that can foresee and possibly prevent future complications within and between organizations. The Handbook of Research on Engineering Innovations and Technology Management in Organizations is a collection of innovative research that explores global concerns in the applications of technology to business and the explosive growth that resulted. Highlighting a wide range of topics such as cyber security, legal practice, and artificial intelligence, this book is ideally designed for engineers, manufacturers, technology managers, technology developers, IT specialists, productivity consultants, executives, lawyers, programmers, managers, policymakers, academicians, researchers, and students. |
computer science and linguistics: Python Algorithms Magnus Lie Hetland, 2014-09-17 Python Algorithms, Second Edition explains the Python approach to algorithm analysis and design. Written by Magnus Lie Hetland, author of Beginning Python, this book is sharply focused on classical algorithms, but it also gives a solid understanding of fundamental algorithmic problem-solving techniques. The book deals with some of the most important and challenging areas of programming and computer science in a highly readable manner. It covers both algorithmic theory and programming practice, demonstrating how theory is reflected in real Python programs. Well-known algorithms and data structures that are built into the Python language are explained, and the user is shown how to implement and evaluate others. |
computer science and linguistics: Machine-aided Linguistic Discovery Vladimir Pericliev, 2010 Solving linguistic problems not infrequently is reduced to carrying out tasks that are computationally complex and therefore requires automation. In such situations, the difference between having and not having computational tools to handle the tasks is not a matter of economy of time and effort, but may amount to the difference between finding and not finding a solution at all. This book is an introduction to machine-aided linguistic discovery, a novel research area, arguing for the fruitfulness of the computational approach by presenting a basic conceptual apparatus and several intelligent discovery programmes. One of the systems models the fundamental Saussurian notion of system, and thus, for the first time, almost a century after the introduction of this concept and structuralism in general, linguists are capable of adequately handling this recurring, computationally complex task. Another system models the problem of searching for Greenbergian language universals and is capable of stating its discoveries in an intelligible form, viz. a comprehensive English language text, thus constituting the first computer program to generate a whole scientific article. Yet another system detects potential inconsistencies in genetic language classifications. The programmes are applied with noteworthy results to substantial problems from diverse linguistic disciplines such as structural semantics, phonology, typology and historical linguistics. |
computer science and linguistics: Human language technologies as a challenge for computer science and linguistics Zygmunt Vetulani, 2007 |
computer science and linguistics: Pragmatics of Computer-Mediated Communication Susan Herring, Dieter Stein, Tuija Virtanen, 2013-01-30 The present handbook provides an overview of the pragmatics of language and language use mediated by digital technologies. Computer-mediated communication (CMC) is defined to include text-based interactive communication via the Internet, websites and other multimodal formats, and mobile communication. In addition to 'core' pragmatic and discourse-pragmatic phenomena the chapters cover pragmatically-focused research on types of CMC and pragmatic approaches to characteristic CMC phenomena. |
computer science and linguistics: Mathematical Linguistics Andras Kornai, 2007-11-10 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. As the first textbook of its kind, this book is useful for those in information science and in natural language technologies. |
computer science and linguistics: Natural Language Processing with Python Steven Bird, Ewan Klein, Edward Loper, 2009-06-12 This book offers a highly accessible introduction to natural language processing, the field that supports a variety of language technologies, from predictive text and email filtering to automatic summarization and translation. With it, you'll learn how to write Python programs that work with large collections of unstructured text. You'll access richly annotated datasets using a comprehensive range of linguistic data structures, and you'll understand the main algorithms for analyzing the content and structure of written communication. Packed with examples and exercises, Natural Language Processing with Python will help you: Extract information from unstructured text, either to guess the topic or identify named entities Analyze linguistic structure in text, including parsing and semantic analysis Access popular linguistic databases, including WordNet and treebanks Integrate techniques drawn from fields as diverse as linguistics and artificial intelligence This book will help you gain practical skills in natural language processing using the Python programming language and the Natural Language Toolkit (NLTK) open source library. If you're interested in developing web applications, analyzing multilingual news sources, or documenting endangered languages -- or if you're simply curious to have a programmer's perspective on how human language works -- you'll find Natural Language Processing with Python both fascinating and immensely useful. |
computer science and linguistics: Quantum Physics and Linguistics Chris Heunen, Mehrnoosh Sadrzadeh, Edward Grefenstette, 2013-02-21 New scientific paradigms typically consist of an expansion of the conceptual language with which we describe the world. Over the past decade, theoretical physics and quantum information theory have turned to category theory to model and reason about quantum protocols. This new use of categorical and algebraic tools allows a more conceptual and insightful expression of elementary events such as measurements, teleportation and entanglement operations, that were obscured in previous formalisms. Recent work in natural language semantics has begun to use these categorical methods to relate grammatical analysis and semantic representations in a unified framework for analysing language meaning, and learning meaning from a corpus. A growing body of literature on the use of categorical methods in quantum information theory and computational linguistics shows both the need and opportunity for new research on the relation between these categorical methods and the abstract notion of information flow. This book supplies an overview of how categorical methods are used to model information flow in both physics and linguistics. It serves as an introduction to this interdisciplinary research, and provides a basis for future research and collaboration between the different communities interested in applying category theoretic methods to their domain's open problems. |
computer science and linguistics: Human Language Technology. Challenges for Computer Science and Linguistics Zygmunt Vetulani, Joseph Mariani, Marek Kubis, 2018-06-15 This book constitutes the refereed proceedings of the 7h Language and Technology Conference: Challenges for Computer Science and Linguistics, LTC 2015, held in Poznan, Poland, in November 2015. The 31 revised papers presented in this volume were carefully reviewed and selected from 108 submissions. The papers selected to this volume belong to various fields of: Speech Processing; Multiword Expressions; Parsing; Language Resources and Tools; Ontologies and Wordnets; Machine Translation; Information and Data Extraction; Text Engineering and Processing; Applications in Language Learning; Emotions, Decisions and Opinions; Less-Resourced Languages. |
computer science and linguistics: Computational approaches to semantic change Nina Tahmasebi, Lars Borin, Adam Jatowt , Yang Xu, Simon Hengchen , 2021-08-30 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. |
Computer - Wikipedia
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Computer - Wikipedia
A computer is a machine that can be programmed to automatically carry out sequences of arithmetic or logical operations (computation). Modern digital electronic computers can …
Computer | Definition, History, Operating Systems, & Facts
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Oct 9, 2024 · A computer is a programmable machine that responds to specific instructions and uses hardware and software to perform tasks. Different types of computers, including …
Computer - Simple English Wikipedia, the free encyclopedia
A computer is a machine that uses electronics to input, process, store, and output data. Data is information such as numbers, words, and lists. Input of data means to read information from a …
Laptop & Desktop Computers - Staples
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What is Computer? Definition, Characteristics and Classification
Aug 7, 2024 · A computer is an electronic device wherein we need to input raw data to be processed with a set of programs to produce a desirable output. Computers have the ability to …