Handbook of Research on Natural Language Processing and Smart Service Systems, Pazos-Rangel Rodolfo Abraham, Florencia-Juarez Rogelio, Paredes-Valverde Mario Andrйs
Автор: Joseph Olive, Caitlin Christianson, John McCary Название: Handbook of Natural Language Processing and Machine Translation ISBN: 1441977120 ISBN-13(EAN): 9781441977120 Издательство: Springer Рейтинг: Цена: 34937.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: 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.
Описание: The Handbook provides a comprehensive overview of the concepts, methodologies, and applications being undertaken today in computational linguistics and natural language processing.
Автор: Zoubida Kedad; Nadira Lammari; Elisabeth M?tais; F Название: Natural Language Processing and Information Systems ISBN: 3540733507 ISBN-13(EAN): 9783540733508 Издательство: Springer Рейтинг: Цена: 13275.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Constitutes the refereed proceedings of the 12th International Conference on Applications of Natural Language to Information Systems, NLDB 2007, held in Paris, France in June 2007. This book covers natural language for database query processing, email management, semantic annotation, text clustering, and ontology engineering.
Автор: M?tais Название: Natural Language Processing and Information Systems ISBN: 3319417533 ISBN-13(EAN): 9783319417530 Издательство: Springer Рейтинг: Цена: 8944.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: 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.
Автор: Goldberg Yoav Название: Neural Network Methods in Natural Language Processing ISBN: 1627052984 ISBN-13(EAN): 9781627052986 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 11504.00 р. Наличие на складе: Нет в наличии.
Описание: Neural networks are a family of powerful machine learning models. This book focuses on the application of neural network models to natural language data. The first half of the book (Parts I and II) covers the basics of supervised machine learning and feed-forward neural networks, the basics of working with machine learning over language data, and the use of vector-based rather than symbolic representations for words. It also covers the computation-graph abstraction, which allows to easily define and train arbitrary neural networks, and is the basis behind the design of contemporary neural network software libraries.The second part of the book (Parts III and IV) introduces more specialized neural network architectures, including 1D convolutional neural networks, recurrent neural networks, conditioned-generation models, and attention-based models. These architectures and techniques are the driving force behind state-of-the-art algorithms for machine translation, syntactic parsing, and many other applications. Finally, we also discuss tree-shaped networks, structured prediction, and the prospects of multi-task learning.
Описание: The concept of narrative has exerted a strong influence on a wide range of fields, from the humanities such as literature (and art and entertainment) to social studies, psychiatry, and psychology. The framework that allows access to narratives across a wide range of areas, from science to the humanities, has the potential to be improved as a fusion of cognitive science and artificial intelligence.
Toward an Integrated Approach to Narrative Generation: Emerging Research and Opportunities is a critical scholarly book that focuses on the significance of narratives and narrative generation in various aspects of human society. Featuring an array of topics such as philosophy, narratology, and advertising, this book is ideal for software developers, academicians, philosophy professionals, researchers, and students in the fields of cognitive studies, literary studies, and digital content design and development.
Описание: Computational linguistics deals with the study of the morphology of language as well as its syntax and dynamic use in order to enable machines process human language. There are numerous applications of this field, such as text-to-speech software, speech recognition and grammar checking. The ability of a computer program to understand human language is known as natural language processing. The two main techniques used with natural language processing are semantic and syntax analysis. Some of the syntax techniques are parsing, word segmentation and sentence breaking. The techniques which are associated with semantics are word sense disambiguation, named entity recognition and natural language generation. This book provides significant information of this discipline to help develop a good understanding of computational linguistics and natural language processing. It will serve as a valuable source of reference for graduate and post graduate students.
Описание: The Handbook provides a comprehensive overview of the concepts, methodologies, and applications being undertaken today in computational linguistics and natural language processing.
Автор: Lotem Peled-Cohen, Roi Reichart, Rotem Dror, Segev Shlomov Название: Statistical Significance Testing for Natural Language Processing ISBN: 1681737957 ISBN-13(EAN): 9781681737959 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 7207.00 р. Наличие на складе: Нет в наличии.
Описание: Data-driven experimental analysis has become the main evaluation tool of Natural Language Processing (NLP) algorithms. In fact, in the last decade, it has become rare to see an NLP paper, particularly one that proposes a new algorithm, that does not include extensive experimental analysis, and the number of involved tasks, datasets, domains, and languages is constantly growing. This emphasis on empirical results highlights the role of statistical significance testing in NLP research: If we, as a community, rely on empirical evaluation to validate our hypotheses and reveal the correct language processing mechanisms, we better be sure that our results are not coincidental.
The goal of this book is to discuss the main aspects of statistical significance testing in NLP. Our guiding assumption throughout the book is that the basic question NLP researchers and engineers deal with is whether or not one algorithm can be considered better than another one. This question drives the field forward as it allows the constant progress of developing better technology for language processing challenges. In practice, researchers and engineers would like to draw the right conclusion from a limited set of experiments, and this conclusion should hold for other experiments with datasets they do not have at their disposal or that they cannot perform due to limited time and resources. The book hence discusses the opportunities and challenges in using statistical significance testing in NLP, from the point of view of experimental comparison between two algorithms. We cover topics such as choosing an appropriate significance test for the major NLP tasks, dealing with the unique aspects of significance testing for non-convex deep neural networks, accounting for a large number of comparisons between two NLP algorithms in a statistically valid manner (multiple hypothesis testing), and, finally, the unique challenges yielded by the nature of the data and practices of the field.
Описание: This book constitutes the refereed proceedings of the 25th International Conference on Applications of Natural Language to Information Systems, NLDB 2020, held in Saarbrucken, Germany, in June 2020.*The 15 full papers and 10 short papers were carefully reviewed and selected from 68 submissions.
Автор: Lotem Peled-Cohen, Roi Reichart, Rotem Dror, Segev Shlomov Название: Statistical Significance Testing for Natural Language Processing ISBN: 1681737973 ISBN-13(EAN): 9781681737973 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 9979.00 р. Наличие на складе: Нет в наличии.
Описание: Data-driven experimental analysis has become the main evaluation tool of Natural Language Processing (NLP) algorithms. In fact, in the last decade, it has become rare to see an NLP paper, particularly one that proposes a new algorithm, that does not include extensive experimental analysis, and the number of involved tasks, datasets, domains, and languages is constantly growing. This emphasis on empirical results highlights the role of statistical significance testing in NLP research: If we, as a community, rely on empirical evaluation to validate our hypotheses and reveal the correct language processing mechanisms, we better be sure that our results are not coincidental.
The goal of this book is to discuss the main aspects of statistical significance testing in NLP. Our guiding assumption throughout the book is that the basic question NLP researchers and engineers deal with is whether or not one algorithm can be considered better than another one. This question drives the field forward as it allows the constant progress of developing better technology for language processing challenges. In practice, researchers and engineers would like to draw the right conclusion from a limited set of experiments, and this conclusion should hold for other experiments with datasets they do not have at their disposal or that they cannot perform due to limited time and resources. The book hence discusses the opportunities and challenges in using statistical significance testing in NLP, from the point of view of experimental comparison between two algorithms. We cover topics such as choosing an appropriate significance test for the major NLP tasks, dealing with the unique aspects of significance testing for non-convex deep neural networks, accounting for a large number of comparisons between two NLP algorithms in a statistically valid manner (multiple hypothesis testing), and, finally, the unique challenges yielded by the nature of the data and practices of the field.
Автор: Christian Kop; G?nther Fliedl; Heinrich C. Mayr; E Название: Natural Language Processing and Information Systems ISBN: 3540346163 ISBN-13(EAN): 9783540346166 Издательство: Springer Рейтинг: Цена: 9083.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Constitutes the proceedings of the 11th International Conference on Applications of Natural Language to Information Systems, NLDB 2006, held in Klagenfurt, Austria in May/June 2006 as part of UNISCON 2006. This book presents papers that are organized in topical sections on concepts extraction and ontology, query processing, and NLP techniques.
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