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Author: Chris Biemann Publisher: Springer Science & Business Media ISBN: 3642259235 Category : Computers Languages : en Pages : 194
Book Description
Current language technology is dominated by approaches that either enumerate a large set of rules, or are focused on a large amount of manually labelled data. The creation of both is time-consuming and expensive, which is commonly thought to be the reason why automated natural language understanding has still not made its way into “real-life” applications yet. This book sets an ambitious goal: to shift the development of language processing systems to a much more automated setting than previous works. A new approach is defined: what if computers analysed large samples of language data on their own, identifying structural regularities that perform the necessary abstractions and generalisations in order to better understand language in the process? After defining the framework of Structure Discovery and shedding light on the nature and the graphic structure of natural language data, several procedures are described that do exactly this: let the computer discover structures without supervision in order to boost the performance of language technology applications. Here, multilingual documents are sorted by language, word classes are identified, and semantic ambiguities are discovered and resolved without using a dictionary or other explicit human input. The book concludes with an outlook on the possibilities implied by this paradigm and sets the methods in perspective to human computer interaction. The target audience are academics on all levels (undergraduate and graduate students, lecturers and professors) working in the fields of natural language processing and computational linguistics, as well as natural language engineers who are seeking to improve their systems.
Author: Chris Biemann Publisher: Springer Science & Business Media ISBN: 3642259235 Category : Computers Languages : en Pages : 194
Book Description
Current language technology is dominated by approaches that either enumerate a large set of rules, or are focused on a large amount of manually labelled data. The creation of both is time-consuming and expensive, which is commonly thought to be the reason why automated natural language understanding has still not made its way into “real-life” applications yet. This book sets an ambitious goal: to shift the development of language processing systems to a much more automated setting than previous works. A new approach is defined: what if computers analysed large samples of language data on their own, identifying structural regularities that perform the necessary abstractions and generalisations in order to better understand language in the process? After defining the framework of Structure Discovery and shedding light on the nature and the graphic structure of natural language data, several procedures are described that do exactly this: let the computer discover structures without supervision in order to boost the performance of language technology applications. Here, multilingual documents are sorted by language, word classes are identified, and semantic ambiguities are discovered and resolved without using a dictionary or other explicit human input. The book concludes with an outlook on the possibilities implied by this paradigm and sets the methods in perspective to human computer interaction. The target audience are academics on all levels (undergraduate and graduate students, lecturers and professors) working in the fields of natural language processing and computational linguistics, as well as natural language engineers who are seeking to improve their systems.
Author: Dioneia Motta Monte-Serrat Publisher: Elsevier ISBN: 0128241187 Category : Computers Languages : en Pages : 252
Book Description
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.
Author: Anne Kao Publisher: Springer Science & Business Media ISBN: 1846287545 Category : Computers Languages : en Pages : 272
Book Description
Natural Language Processing and Text Mining not only discusses applications of Natural Language Processing techniques to certain Text Mining tasks, but also the converse, the use of Text Mining to assist NLP. It assembles a diverse views from internationally recognized researchers and emphasizes caveats in the attempt to apply Natural Language Processing to text mining. This state-of-the-art survey is a must-have for advanced students, professionals, and researchers.
Author: Rada Mihalcea Publisher: Cambridge University Press ISBN: 1139498827 Category : Computers Languages : en Pages : 201
Book Description
Graph theory and the fields of natural language processing and information retrieval are well-studied disciplines. Traditionally, these areas have been perceived as distinct, with different algorithms, different applications and different potential end-users. However, recent research has shown that these disciplines are intimately connected, with a large variety of natural language processing and information retrieval applications finding efficient solutions within graph-theoretical frameworks. This book extensively covers the use of graph-based algorithms for natural language processing and information retrieval. It brings together topics as diverse as lexical semantics, text summarization, text mining, ontology construction, text classification and information retrieval, which are connected by the common underlying theme of the use of graph-theoretical methods for text and information processing tasks. Readers will come away with a firm understanding of the major methods and applications in natural language processing and information retrieval that rely on graph-based representations and algorithms.
Author: Tanwar, Poonam Publisher: IGI Global ISBN: 1799877302 Category : Computers Languages : en Pages : 240
Book Description
To sustain and stay at the top of the market and give absolute comfort to the consumers, industries are using different strategies and technologies. Natural language processing (NLP) is a technology widely penetrating the market, irrespective of the industry and domains. It is extensively applied in businesses today, and it is the buzzword in every engineer’s life. NLP can be implemented in all those areas where artificial intelligence is applicable either by simplifying the communication process or by refining and analyzing information. Neural machine translation has improved the imitation of professional translations over the years. When applied in neural machine translation, NLP helps educate neural machine networks. This can be used by industries to translate low-impact content including emails, regulatory texts, etc. Such machine translation tools speed up communication with partners while enriching other business interactions. Deep Natural Language Processing and AI Applications for Industry 5.0 provides innovative research on the latest findings, ideas, and applications in fields of interest that fall under the scope of NLP including computational linguistics, deep NLP, web analysis, sentiments analysis for business, and industry perspective. This book covers a wide range of topics such as deep learning, deepfakes, text mining, blockchain technology, and more, making it a crucial text for anyone interested in NLP and artificial intelligence, including academicians, researchers, professionals, industry experts, business analysts, data scientists, data analysts, healthcare system designers, intelligent system designers, practitioners, and students.
Author: Philip M. McCarthy Publisher: IGI Global ISBN: 9781609607418 Category : Computers Languages : en Pages : 0
Book Description
"This book offers a description of ANLP: what it is, what it does; and where it's going, including defining the role of ANLP within NLP, and alongside other disciplines such as linguistics, computer science, and cognitive science"--Provided by publisher.
Author: Juergen Weissenborn Publisher: Psychology Press ISBN: 1134746695 Category : Language Arts & Disciplines Languages : en Pages : 334
Book Description
In recent linguistic theory, there has been an explosion of detailed studies of language variation. This volume applies such recent analyses to the study of child language, developing new approaches to change and variation in child grammars and revealing both early knowledge in several areas of grammar and a period of extended development in others. Topics dealt with include question formation, "subjectless" sentences, object gaps, rules for missing subject interpretation, passive sentences, rules for pronoun interpretation and argument structure. Leading developmental linguists and psycholinguists show how linguistic theory can help define and inform a theory of the dynamics of language development and its biological basis, meeting the growing need for such studies in programs in linguistics, psychology, and cognitive science.
Author: Elisabeth Métais Publisher: Springer ISBN: 3319417541 Category : Computers Languages : en Pages : 498
Book Description
This book constitutes the refereed proceedings of the 21st International Conference on Applications of Natural Language to Information Systems, NLDB 2016, held in Salford, UK, in June 2016. The 17 full papers, 22 short papers, and 13 poster papers presented were carefully reviewed and selected from 83 submissions. The papers cover the following topics: theoretical aspects, algorithms, applications, architectures for applied and integrated NLP, resources for applied NLP, and other aspects of NLP.
Author: Norbert E Fuchs Publisher: Springer ISBN: 3642144187 Category : Computers Languages : en Pages : 299
Book Description
Controlled natural languages (CNLs) are subsets of natural languages, obtained by - stricting the grammar and vocabulary in order to reduce or eliminate ambiguity and complexity. Traditionally, controlled languagesfall into two major types: those that - prove readability for human readers, and those that enable reliable automatic semantic analysis of the language. [. . . ] The second type of languages has a formal logical basis, i. e. they have a formal syntax and semantics, and can be mapped to an existing formal language, such as ?rst-order logic. Thus, those languages can be used as knowledge representation languages, and writing of those languages is supported by fully au- matic consistency and redundancy checks, query answering, etc. Wikipedia Variouscontrollednatural languagesof the second type have been developedby a n- ber of organizations, and have been used in many different application domains, most recently within the Semantic Web. The workshop CNL 2009 was dedicated to discussing the similarities and the d- ferences of existing controlled natural languages of the second type, possible impro- ments to these languages, relations to other knowledge representation languages, tool support, existing and future applications, and further topics of interest.
Author: Chris Biemann
Author: Chris Biemann
Author: Dioneia Motta Monte-Serrat
Author: Anne Kao
Author: Rada Mihalcea
Author: Tanwar, Poonam
Author: Philip M. McCarthy
Author: Juergen Weissenborn
Author: Elisabeth Métais
Author: Rudolf P. Botha
Author: Norbert E Fuchs