Embeddings in natural language processing, Pilehvar, Mohammad Taher Camacho-collados, Jose
Автор: Maosong Sun, Xiaojie Wang, Baobao Chang Название: Chinese Computational Linguistics and Natural Language Processing Based on Naturally Annotated Big Data ISBN: 3319690043 ISBN-13(EAN): 9783319690049 Издательство: Springer Рейтинг: Цена: 35330.00 T Наличие на складе: Есть Описание: This book constitutes the proceedings of the 16th China National Conference on Computational Linguistics, CCL 2017, and the 5th International Symposium on Natural Language Processing Based on Naturally Annotated Big Data, NLP-NABD 2017, held in Nanjing, China, in October 2017. Minority language information processing.
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: 232910.00 T 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.
Автор: Bhavsar Krishnakumar, Dangeti Pratap Название: Natural Language Processing with Python Cookbook ISBN: 178728932X ISBN-13(EAN): 9781787289321 Издательство: Неизвестно Рейтинг: Цена: 36770.00 T Наличие на складе: Нет в наличии.
Автор: Paul Mc Kevitt Название: Integration of Natural Language and Vision Processing ISBN: 0792333799 ISBN-13(EAN): 9780792333791 Издательство: Springer Рейтинг: Цена: 144410.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This collection contains a set of edited papers addressing computational models and systems for the integration of natural language processing and vision processing. The papers focus on site descriptions such as that of the large Japanese $500 million Real World Computing (RWC) project.
Автор: Sogaard Anders, Vulic Ivan, Ruder Sebastian Название: Cross-Lingual Word Embeddings ISBN: 1681730634 ISBN-13(EAN): 9781681730639 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 61910.00 T Наличие на складе: Невозможна поставка. Описание:
The majority of natural language processing (NLP) is English language processing, and while there is good language technology support for (standard varieties of) English, support for Albanian, Burmese, or Cebuano-and most other languages-remains limited.
Being able to bridge this digital divide is important for scientific and democratic reasons but also represents an enormous growth potential. A key challenge for this to happen is learning to align basic meaning-bearing units of different languages.
In this book, the authors survey and discuss recent and historical work on supervised and unsupervised learning of such alignments. Specifically, the book focuses on so-called cross-lingual word embeddings. The survey is intended to be systematic, using consistent notation and putting the available methods on comparable form, making it easy to compare wildly different approaches. In so doing, the authors establish previously unreported relations between these methods and are able to present a fast-growing literature in a very compact way. Furthermore, the authors discuss how best to evaluate cross-lingual word embedding methods and survey the resources available for students and researchers interested in this topic.
Автор: Pilehvar, Mohammad Taher Camacho-collados, Jose Название: Embeddings in natural language processing ISBN: 1636390218 ISBN-13(EAN): 9781636390215 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 61910.00 T Наличие на складе: Нет в наличии. Описание: Provides a high-level synthesis of the main embedding techniques in NLP, in the broad sense. The book starts by explaining conventional word vector space models and word embeddings (e.g., Word2Vec and GloVe) and then moves to other types of embeddings, such as word sense, sentence and document, and graph embeddings.
Автор: Sogaard Anders, Vulic Ivan, Ruder Sebastian Название: Cross-Lingual Word Embeddings ISBN: 1681735725 ISBN-13(EAN): 9781681735726 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 82230.00 T Наличие на складе: Невозможна поставка. Описание:
The majority of natural language processing (NLP) is English language processing, and while there is good language technology support for (standard varieties of) English, support for Albanian, Burmese, or Cebuano-and most other languages-remains limited.
Being able to bridge this digital divide is important for scientific and democratic reasons but also represents an enormous growth potential. A key challenge for this to happen is learning to align basic meaning-bearing units of different languages.
In this book, the authors survey and discuss recent and historical work on supervised and unsupervised learning of such alignments. Specifically, the book focuses on so-called cross-lingual word embeddings. The survey is intended to be systematic, using consistent notation and putting the available methods on comparable form, making it easy to compare wildly different approaches. In so doing, the authors establish previously unreported relations between these methods and are able to present a fast-growing literature in a very compact way. Furthermore, the authors discuss how best to evaluate cross-lingual word embedding methods and survey the resources available for students and researchers interested in this topic.
Автор: Abhijit Mishra, Pushpak Bhattacharyya Название: Cognitively Inspired Natural Language Processing ISBN: 9811315159 ISBN-13(EAN): 9789811315152 Издательство: Springer Рейтинг: Цена: 93160.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book shows ways of augmenting the capabilities of Natural Language Processing (NLP) systems by means of cognitive-mode language processing.
Автор: Rao Delip Название: Natural Language Processing with Pytorch: Build Intelligent Language Applications Using Deep Learning ISBN: 1491978236 ISBN-13(EAN): 9781491978238 Издательство: Wiley Рейтинг: Цена: 76020.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: If you`re a developer or data scientist new to NLP and deep learning, this practical guide shows you how to apply these methods using PyTorch, a Python-based deep learning library.
Автор: Goldberg Yoav Название: Neural Network Methods in Natural Language Processing ISBN: 1627052984 ISBN-13(EAN): 9781627052986 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 76690.00 T 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.
Автор: Dimitris N. Christodoulakis Название: Natural Language Processing - NLP 2000 ISBN: 3540676058 ISBN-13(EAN): 9783540676058 Издательство: Springer Рейтинг: Цена: 81050.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This volume constitutes the refereed proceedings of the Second International Conference on Natural Language Processing, NLP 2000. Topics covered include: tokenization and morphological analysis; lexical knowledge representation; parsing and discourse analysis; and anaphora resolution.
Автор: Waltz David L. Название: Semantic Structures (Rle Linguistics B: Grammar): Advances in Natural Language Processing ISBN: 113898163X ISBN-13(EAN): 9781138981638 Издательство: Taylor&Francis Рейтинг: Цена: 46950.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Natural language understanding is central to the goals of artificial intelligence. Any truly intelligent machine must be capable of carrying on a conversation: dialogue, particularly clarification dialogue, is essential if we are to avoid disasters caused by the misunderstanding of the intelligent interactive systems of the future. This book is an interim report on the grand enterprise of devising a machine that can use natural language as fluently as a human. What has really been achieved since this goal was first formulated in Turing’s famous test? What obstacles still need to be overcome?
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