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Book Linguistic Approaches to Artificial Intelligence

Download or read book Linguistic Approaches to Artificial Intelligence written by Ulrich Schmitz and published by Peter Lang Gmbh, Internationaler Verlag Der Wissenschaften. This book was released on 1990 with total page 574 pages. Available in PDF, EPUB and Kindle. Book excerpt: Lately some important scientific innovations have come from dialogues and discussions between human sciences and the more technically oriented fields of research. This especially applies to the border area of linguistics and artificial intelligence research work. The book gives a representative insight into the state-of-the-art. Still there are very few common ideas between linguistic interests and the challenges of artificial intelligence. Nevertheless numerous communications between linguistic, cognitive, psychological approaches and those of the computer sciences, as well as further single aspects come into sight. The contributions deal with problems belonging to the fields of psycholinguistics, discourse analysis, text linguistics and semantics, semantic representation, knowledge representation and knowledge acquisition, unification theory and unification grammar, construction of parsers and grammar theory, natural language processing, speech analysis and text generating systems, machine translation and the differences between man-man and man-machine communication.

Book Linguistics for the Age of AI

Download or read book Linguistics for the Age of AI written by Marjorie Mcshane and published by MIT Press. This book was released on 2021-03-02 with total page 449 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book Linguistics for the Age of AI

Download or read book Linguistics for the Age of AI written by Marjorie Mcshane and published by MIT Press. This book was released on 2021-03-02 with total page 449 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book New Methods In Language Processing

Download or read book New Methods In Language Processing written by D. B. Jones and published by Routledge. This book was released on 2013-11-05 with total page 385 pages. Available in PDF, EPUB and Kindle. Book excerpt: Studies in Computational Linguistics presents authoritative texts from an international team of leading computational linguists. The books range from the senior undergraduate textbook to the research level monograph and provide a showcase for a broad range of recent developments in the field. The series should be interesting reading for researchers and students alike involved at this interface of linguistics and computing.

Book The Natural Language for Artificial Intelligence

Download or read book The Natural Language for Artificial Intelligence written by Dioneia Motta Monte-Serrat and published by Elsevier. This book was released on 2021-04-06 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Natural Language for Artificial Intelligence presents natural language as the next frontier because it identifies something that is most sought after by scholars: The universal structure of language that gives rise to the respective universal algorithm. In short, this book presents the biological and logical structure typical of human language in its dynamic mediating process between reality and the human mind that, at the same time, interprets the context of reality. It is a non-static approach to natural language, which is defined as a complex system whose parts interact with the ability to generate a new quality of behavior and whose dynamic elements are mapped in order to be understood and executed by intelligent systems, guiding the paradigms of cognitive computing. The book explains linguistic functioning in the dynamic process of human cognition when forming meaning. After that, an approach to artificial intelligence (AI) is outlined, which works with a more restricted concept of natural language, leading to flaws and ambiguities. Subsequently, the characteristics of natural language and patterns of how it behaves in different branches of science are revealed, to indicate ways to improve the development of AI in specific fields of science. A brief description of the universal structure of language is also presented as an algorithmic model to be followed in the development of AI. Since AI aims to imitate the process of the human mind, the book shows how the cross-fertilization between natural language and AI should be done using the logical-axiomatic structure of natural language adjusted to the logical-mathematical processes of the machine.

Book Empirical Methods in Natural Language Generation

Download or read book Empirical Methods in Natural Language Generation written by Emiel Krahmer and published by Springer Science & Business Media. This book was released on 2010-09-09 with total page 363 pages. Available in PDF, EPUB and Kindle. Book excerpt: Natural language generation (NLG) is a subfield of natural language processing (NLP) that is often characterized as the study of automatically converting non-linguistic representations (e.g., from databases or other knowledge sources) into coherent natural language text. In recent years the field has evolved substantially. Perhaps the most important new development is the current emphasis on data-oriented methods and empirical evaluation. Progress in related areas such as machine translation, dialogue system design and automatic text summarization and the resulting awareness of the importance of language generation, the increasing availability of suitable corpora in recent years, and the organization of shared tasks for NLG, where different teams of researchers develop and evaluate their algorithms on a shared, held out data set have had a considerable impact on the field, and this book offers the first comprehensive overview of recent empirically oriented NLG research.

Book Computational Grammar

Download or read book Computational Grammar written by Graeme D. Ritchie and published by . This book was released on 1980 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Connectionist  Statistical and Symbolic Approaches to Learning for Natural Language Processing

Download or read book Connectionist Statistical and Symbolic Approaches to Learning for Natural Language Processing written by Stefan Wermter and published by Springer Science & Business Media. This book was released on 1996-03-15 with total page 490 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is based on the workshop on New Approaches to Learning for Natural Language Processing, held in conjunction with the International Joint Conference on Artificial Intelligence, IJCAI'95, in Montreal, Canada in August 1995. Most of the 32 papers included in the book are revised selected workshop presentations; some papers were individually solicited from members of the workshop program committee to give the book an overall completeness. Also included, and written with the novice reader in mind, is a comprehensive introductory survey by the volume editors. The volume presents the state of the art in the most promising current approaches to learning for NLP and is thus compulsory reading for researchers in the field or for anyone applying the new techniques to challenging real-world NLP problems.

Book Machine aided Linguistic Discovery

Download or read book Machine aided Linguistic Discovery written by Vladimir Pericliev and published by Equinox Publishing (UK). This book was released on 2010 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book Deep Learning and Linguistic Representation

Download or read book Deep Learning and Linguistic Representation written by Shalom Lappin and published by CRC Press. This book was released on 2021-04-26 with total page 162 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book Modelling Spatial Knowledge on a Linguistic Basis

Download or read book Modelling Spatial Knowledge on a Linguistic Basis written by Ewald Lang and published by Springer. This book was released on 1991 with total page 156 pages. Available in PDF, EPUB and Kindle. Book excerpt: "On the basis of a semantic analysis of dimension terms, this book develops a theory about knowledge of spatial objects, which is significant for cognitive linguistics and artificial intelligence. This new approach to knowledge structure evolves in a three-step process: - adoption of the linguistic theory with its elements, principles and representational levels, - implementation of the latter in a Prolog prototype, and - integration of the prototype into a large natural language understanding system. The study documents interdisciplinary research at work: the model of spatial knowledge is the fruit of the cooperative efforts of linguists, computational linguists, and knowledge engineers, undertaken in that logical and chronological order. The book offers a two-level approach to semantic interpretation and proves that it works by means of a precise computer implementation, which in turn is applied to support a task-independent knowledge representation system. Each of these stages is described in detail, and the links are made explicit, thus retracing the evolution from theory to practice."--PUBLISHER'S WEBSITE.

Book Interdisciplinary Approaches to Language

Download or read book Interdisciplinary Approaches to Language written by C. Georgopoulos and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 681 pages. Available in PDF, EPUB and Kindle. Book excerpt: The thirty-two papers in this collection are offered to Professor S.-Y. Kuroda by his friends, as a ge sture of their deep respect and enduring affection. One of the many ways in which Professor Kuroda has impressed us all is in the breadth of his interests and areas of expertise. He is one of those rare scholars whose work and interests span the whole range of his discipline. He is a figure of such intellectual stature that he has inspired, influenced, and encouraged researchers in an astonishing variety of projects. He continues to do so at an unslackened pace today, just as his own productivity remains vigorous. But mention of Yuki's inspiration and influence is inadequate without mention of his special humorousness, his mischievous wit, his charm and as a friend, has added a unique warmth. Knowing Yuki, and counting him quality to our lives. We who have contributed to this collection have done so in partial acknowledgement of, and gratitude for, this benign and masterful influence. The contributions to the collection reflect the range of Yuki's own interests, and cover a rich variety of approaches to the analysis of natural language. These include papers in philosophy, psychology, computer sciencel artificial intelligence, and linguistics, and, within linguistics, the entire breadth of the field: phonology, morphology, syntax, semantics, pragmatics, and computation. Though diverse in their themes, language areas, and foci, the papers are bound by their authors' common bond to Yuki.

Book Modelling with Words

    Book Details:
  • Author : Jonathan Lawry
  • Publisher : Springer
  • Release : 2003-10-28
  • ISBN : 3540399062
  • Pages : 241 pages

Download or read book Modelling with Words written by Jonathan Lawry and published by Springer. This book was released on 2003-10-28 with total page 241 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modelling with Words is an emerging modelling methodology closely related to the paradigm of Computing with Words introduced by Lotfi Zadeh. This book is an authoritative collection of key contributions to the new concept of Modelling with Words. A wide range of issues in systems modelling and analysis is presented, extending from conceptual graphs and fuzzy quantifiers to humanist computing and self-organizing maps. Among the core issues investigated are - balancing predictive accuracy and high level transparency in learning - scaling linguistic algorithms to high-dimensional data problems - integrating linguistic expert knowledge with knowledge derived from data - identifying sound and useful inference rules - integrating fuzzy and probabilistic uncertainty in data modelling

Book Automatic Language Identification in Texts

Download or read book Automatic Language Identification in Texts written by Tommi Jauhiainen and published by Springer Nature. This book was released on 2024-02-02 with total page 155 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides readers with a brief account of the history of Language Identification (LI) research and a survey of the features and methods most used in LI literature. LI is the problem of determining the language in which a document is written and is a crucial part of many text processing pipelines. The authors use a unified notation to clarify the relationships between common LI methods. The book introduces LI performance evaluation methods and takes a detailed look at LI-related shared tasks. The authors identify open issues and discuss the applications of LI and related tasks and proposes future directions for research in LI.

Book Natural Language Processing in Artificial Intelligence

Download or read book Natural Language Processing in Artificial Intelligence written by Brojo Kishore Mishra and published by CRC Press. This book was released on 2020-11-01 with total page 297 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume focuses on natural language processing, artificial intelligence, and allied areas. Natural language processing enables communication between people and computers and automatic translation to facilitate easy interaction with others around the world. This book discusses theoretical work and advanced applications, approaches, and techniques for computational models of information and how it is presented by language (artificial, human, or natural) in other ways. It looks at intelligent natural language processing and related models of thought, mental states, reasoning, and other cognitive processes. It explores the difficult problems and challenges related to partiality, underspecification, and context-dependency, which are signature features of information in nature and natural languages. Key features: Addresses the functional frameworks and workflow that are trending in NLP and AI Looks at the latest technologies and the major challenges, issues, and advances in NLP and AI Explores an intelligent field monitoring and automated system through AI with NLP and its implications for the real world Discusses data acquisition and presents a real-time case study with illustrations related to data-intensive technologies in AI and NLP.

Book Introduction to Natural Language Processing

Download or read book Introduction to Natural Language Processing written by Jacob Eisenstein and published by MIT Press. This book was released on 2019-10-01 with total page 535 pages. Available in PDF, EPUB and Kindle. Book excerpt: A survey of computational methods for understanding, generating, and manipulating human language, which offers a synthesis of classical representations and algorithms with contemporary machine learning techniques. This textbook provides a technical perspective on natural language processing—methods for building computer software that understands, generates, and manipulates human language. It emphasizes contemporary data-driven approaches, focusing on techniques from supervised and unsupervised machine learning. The first section establishes a foundation in machine learning by building a set of tools that will be used throughout the book and applying them to word-based textual analysis. The second section introduces structured representations of language, including sequences, trees, and graphs. The third section explores different approaches to the representation and analysis of linguistic meaning, ranging from formal logic to neural word embeddings. The final section offers chapter-length treatments of three transformative applications of natural language processing: information extraction, machine translation, and text generation. End-of-chapter exercises include both paper-and-pencil analysis and software implementation. The text synthesizes and distills a broad and diverse research literature, linking contemporary machine learning techniques with the field's linguistic and computational foundations. It is suitable for use in advanced undergraduate and graduate-level courses and as a reference for software engineers and data scientists. Readers should have a background in computer programming and college-level mathematics. After mastering the material presented, students will have the technical skill to build and analyze novel natural language processing systems and to understand the latest research in the field.