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Machine-aided Linguistic Discovery

Author : Vladimir Pericliev
Publisher : Equinox Publishing (UK)
Page : 0 pages
File Size : 39,45 MB
Release : 2010
Category : Computational linguistics
ISBN : 9781845536602

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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.

Componential Analysis of Kinship Terminology

Author : V. Pericliev
Publisher : Springer
Page : 169 pages
File Size : 32,93 MB
Release : 2013-07-26
Category : Language Arts & Disciplines
ISBN : 1137031182

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This book presents the first computer program automating the task of componential analysis of kinship vocabularies. The book examines the program in relation to two basic problems: the commonly occurring inconsistency of componential models; and the huge number of alternative componential models.

Machine Learning of Natural Language

Author : David M.W. Powers
Publisher : Springer Science & Business Media
Page : 361 pages
File Size : 15,32 MB
Release : 2012-12-06
Category : Computers
ISBN : 1447116976

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We met because we both share the same views of language. Language is a living organism, produced by neural mechanisms relating in large numbers as a society. Language exists between minds, as a way of communicating between them, not as an autonomous process. The logical 'rules' seem to us an epiphe nomena ·of the neural mechanism, rather than an essential component in language. This view of language has been advocated by an increasing number of workers, as the view that language is simply a collection of logical rules has had less and less success. People like Yorick Wilks have been able to show in paper after paper that almost any rule which can be devised can be shown to have exceptions. The meaning does not lie in the rules. David Powers is a teacher of computer science. Christopher Turk, like many workers who have come into the field of AI (Artificial Intelligence) was originally trained in literature. He moved into linguistics, and then into computational linguistics. In 1983 he took a sabbatical in Roger Shank's AI project in the Computer Science Department at Yale University. Like an earlier visitor to the project, John Searle from California, Christopher Turk was increasingly uneasy at the view of language which was used at Yale.

Modern Computational Models of Semantic Discovery in Natural Language

Author : Žižka, Jan
Publisher : IGI Global
Page : 353 pages
File Size : 48,31 MB
Release : 2015-07-17
Category : Computers
ISBN : 146668691X

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Language—that is, oral or written content that references abstract concepts in subtle ways—is what sets us apart as a species, and in an age defined by such content, language has become both the fuel and the currency of our modern information society. This has posed a vexing new challenge for linguists and engineers working in the field of language-processing: how do we parse and process not just language itself, but language in vast, overwhelming quantities? Modern Computational Models of Semantic Discovery in Natural Language compiles and reviews the most prominent linguistic theories into a single source that serves as an essential reference for future solutions to one of the most important challenges of our age. This comprehensive publication benefits an audience of students and professionals, researchers, and practitioners of linguistics and language discovery. This book includes a comprehensive range of topics and chapters covering digital media, social interaction in online environments, text and data mining, language processing and translation, and contextual documentation, among others.

Language

Author : George Melville Bolling
Publisher :
Page : 566 pages
File Size : 37,19 MB
Release : 2010
Category : Comparative linguistics
ISBN :

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Proceedings of the annual meeting of the Society in v. 1-11, 1925-34. After 1934 they appear in Its Bulletin.

Handbook of Natural Language Processing and Machine Translation

Author : Joseph Olive
Publisher : Springer Science & Business Media
Page : 956 pages
File Size : 48,41 MB
Release : 2011-03-02
Category : Computers
ISBN : 1441977139

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This comprehensive handbook, written by leading experts in the field, details the groundbreaking research conducted under the breakthrough GALE program--The Global Autonomous Language Exploitation within the Defense Advanced Research Projects Agency (DARPA), while placing it in the context of previous research in the fields of natural language and signal processing, artificial intelligence and machine translation. The most fundamental contrast between GALE and its predecessor programs was its holistic integration of previously separate or sequential processes. In earlier language research programs, each of the individual processes was performed separately and sequentially: speech recognition, language recognition, transcription, translation, and content summarization. The GALE program employed a distinctly new approach by executing these processes simultaneously. Speech and language recognition algorithms now aid translation and transcription processes and vice versa. This combination of previously distinct processes has produced significant research and performance breakthroughs and has fundamentally changed the natural language processing and machine translation fields. This comprehensive handbook provides an exhaustive exploration into these latest technologies in natural language, speech and signal processing, and machine translation, providing researchers, practitioners and students with an authoritative reference on the topic.

Discovery Science

Author : Gunter Grieser
Publisher : Springer Science & Business Media
Page : 515 pages
File Size : 44,14 MB
Release : 2003-10-07
Category : Business & Economics
ISBN : 3540202935

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This book constitutes the refereed proceedings of the 6th International Conference on Discovery Science, DS 2003, held in Sapporo, Japan in October 2003. The 18 revised full papers and 29 revised short papers presented together with 3 invited papers and abstracts of 2 invited talks were carefully reviewed and selected from 80 submissions. The papers address all current issues in discovery science including substructure discovery, Web navigation patterns discovery, graph-based induction, time series data analysis, rough sets, genetic algorithms, clustering, genome analysis, chaining patterns, association rule mining, classification, content based filtering, bioinformatics, case-based reasoning, text mining, Web data analysis, and more.

A Handbook of Computational Linguistics: Artificial Intelligence in Natural Language Processing

Author : Youddha Beer Singh
Publisher : Bentham Science Publishers
Page : 394 pages
File Size : 18,56 MB
Release : 2024-08-12
Category : Computers
ISBN : 9815238493

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This handbook provides a comprehensive understanding of computational linguistics, focusing on the integration of deep learning in natural language processing (NLP). 18 edited chapters cover the state-of-the-art theoretical and experimental research on NLP, offering insights into advanced models and recent applications. Highlights: - Foundations of NLP: Provides an in-depth study of natural language processing, including basics, challenges, and applications. - Advanced NLP Techniques: Explores recent advancements in text summarization, machine translation, and deep learning applications in NLP. - Practical Applications: Demonstrates use cases on text identification from hazy images, speech-to-sign language translation, and word sense disambiguation using deep learning. - Future Directions: Includes discussions on the future of NLP, including transfer learning, beyond syntax and semantics, and emerging challenges. Key Features: - Comprehensive coverage of NLP and deep learning integration. - Practical insights into real-world applications - Detailed exploration of recent research and advancements through 16 easy to read chapters - References and notes on experimental methods used for advanced readers Ideal for researchers, students, and professionals, this book offers a thorough understanding of computational linguistics by equipping readers with the knowledge to understand how computational techniques are applied to understand text, language and speech.

Linguistic Linked Data

Author : Philipp Cimiano
Publisher : Springer
Page : 280 pages
File Size : 24,17 MB
Release : 2020-01-05
Category : Computers
ISBN : 9783030302245

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This is the first monograph on the emerging area of linguistic linked data. Presenting a combination of background information on linguistic linked data and concrete implementation advice, it introduces and discusses the main benefits of applying linked data (LD) principles to the representation and publication of linguistic resources, arguing that LD does not look at a single resource in isolation but seeks to create a large network of resources that can be used together and uniformly, and so making more of the single resource. The book describes how the LD principles can be applied to modelling language resources. The first part provides the foundation for understanding the remainder of the book, introducing the data models, ontology and query languages used as the basis of the Semantic Web and LD and offering a more detailed overview of the Linguistic Linked Data Cloud. The second part of the book focuses on modelling language resources using LD principles, describing how to model lexical resources using Ontolex-lemon, the lexicon model for ontologies, and how to annotate and address elements of text represented in RDF. It also demonstrates how to model annotations, and how to capture the metadata of language resources. Further, it includes a chapter on representing linguistic categories. In the third part of the book, the authors describe how language resources can be transformed into LD and how links can be inferred and added to the data to increase connectivity and linking between different datasets. They also discuss using LD resources for natural language processing. The last part describes concrete applications of the technologies: representing and linking multilingual wordnets, applications in digital humanities and the discovery of language resources. Given its scope, the book is relevant for researchers and graduate students interested in topics at the crossroads of natural language processing / computational linguistics and the Semantic Web / linked data. It appeals to Semantic Web experts who are not proficient in applying the Semantic Web and LD principles to linguistic data, as well as to computational linguists who are used to working with lexical and linguistic resources wanting to learn about a new paradigm for modelling, publishing and exploiting linguistic resources.