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Quality Estimation for Machine Translation, Lucia Specia, Carolina Scarton, Gustavo Henrique Paetzold


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Автор: Lucia Specia, Carolina Scarton, Gustavo Henrique Paetzold
Название:  Quality Estimation for Machine Translation
ISBN: 9781681733753
Издательство: Mare Nostrum (Eurospan)
Классификация:


ISBN-10: 1681733757
Обложка/Формат: Hardcover
Страницы: 162
Вес: 0.50 кг.
Дата издания: 30.09.2018
Серия: Synthesis lectures on human language technologies
Язык: English
Размер: 235 x 191 x 11
Ключевые слова: Computer science,Artificial intelligence,Natural language & machine translation, COMPUTERS / Intelligence (AI) & Semantics,COMPUTERS / Natural Language Processing,COMPUTERS / Programming / Algorithms
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Поставляется из: Англии
Описание: Many applications within natural language processing involve performing text-to-text transformations, i.e., given a text in natural language as input, systems are required to produce a version of this text (e.g., a translation), also in natural language, as output. Automatically evaluating the output of such systems is an important component in developing text-to-text applications. Two approaches have been proposed for this problem: (i) to compare the system outputs against one or more reference outputs using string matching-based evaluation metrics and (ii) to build models based on human feedback to predict the quality of system outputs without reference texts. Despite their popularity, reference-based evaluation metrics are faced with the challenge that multiple good (and bad) quality outputs can be produced by text-to-text approaches for the same input. This variation is very hard to capture, even with multiple reference texts. In addition, reference-based metrics cannot be used in production (e.g., online machine translation systems), when systems are expected to produce outputs for any unseen input. In this book, we focus on the second set of metrics, so-called Quality Estimation (QE) metrics, where the goal is to provide an estimate on how good or reliable the texts produced by an application are without access to gold-standard outputs. QE enables different types of evaluation that can target different types of users and applications. Machine learning techniques are used to build QE models with various types of quality labels and explicit features or learnt representations, which can then predict the quality of unseen system outputs. This book describes the topic of QE for text-to-text applications, covering quality labels, features, algorithms, evaluation, uses, and state-of-the-art approaches. It focuses on machine translation as application, since this represents most of the QE work done to date. It also briefly describes QE for several other applications, including text simplification, text summarization, grammatical error correction, and natural language generation.

Handbook of Natural Language Processing and Machine Translation

Автор: Joseph Olive, Caitlin Christianson, John McCary
Название: Handbook of Natural Language Processing and Machine Translation
ISBN: 1441977120 ISBN-13(EAN): 9781441977120
Издательство: Springer
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Цена: 232910.00 T
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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.

Automated Planning and Acting

Автор: Ghallab
Название: Automated Planning and Acting
ISBN: 1107037271 ISBN-13(EAN): 9781107037274
Издательство: Cambridge Academ
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Цена: 70750.00 T
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Описание: Autonomous AI systems need complex computational techniques for planning and performing actions. This textbook presents the most recent and advanced techniques within the field that allow systems such as the Mars rovers, intelligent harbor-management systems, or self-driving cards to act effectively in the real world.

An Introduction to Machine Learning

Автор: Miroslav Kubat
Название: An Introduction to Machine Learning
ISBN: 3319348868 ISBN-13(EAN): 9783319348865
Издательство: Springer
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Цена: 46570.00 T
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Описание: This book presents basic ideas of machine learning in a way that is easy to understand, by providing hands-on practical advice, using simple examples, and motivating students with discussions of interesting applications.

Principles of Automated Negotiation

Автор: Fatima
Название: Principles of Automated Negotiation
ISBN: 1107002540 ISBN-13(EAN): 9781107002548
Издательство: Cambridge Academ
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Цена: 50680.00 T
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Описание: With an increasing number of applications in the context of multi-agent systems, automated negotiation is a rapidly growing area. Written by top researchers in the field, this state-of-the-art treatment of the subject explores key issues involved in the design of negotiating agents, covering strategic, heuristic, and axiomatic approaches. The authors discuss the potential benefits of automated negotiation as well as the unique challenges it poses for computer scientists and for researchers in artificial intelligence. They also consider possible applications and give readers a feel for the types of domains where automated negotiation is already being deployed. This book is ideal for graduate students and researchers in computer science who are interested in multi-agent systems. It will also appeal to negotiation researchers from disciplines such as management and business studies, psychology and economics.

Social Network Engineering For Secure Web Data And Services

Автор: Caviglione, Coccoli & Merlo
Название: Social Network Engineering For Secure Web Data And Services
ISBN: 1466639261 ISBN-13(EAN): 9781466639263
Издательство: Mare Nostrum (Eurospan)
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Цена: 189420.00 T
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Описание: While the innovation and phenomenon of social network applications has greatly impacted society, the economy, and the technological pool of the internet; these platforms are not only used for content sharing purposes. They are also used to support and develop new services and applications. <em>Social Network Engineering for Secure Web Data and Services</em> provides empirical research on the engineering of social network infrastructures, the development of novel applications, and the impact of social network- based services over the internet. This comprehensive collection highlights issues and solutions developed to prevent security threats and introduce proper countermeasures for attacks on every level. This book is useful for professionals and researchers in the field of social network and web security.

Hybrid Approaches to Machine Translation

Автор: Costa-juss?
Название: Hybrid Approaches to Machine Translation
ISBN: 3319213105 ISBN-13(EAN): 9783319213101
Издательство: Springer
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Цена: 79190.00 T
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Описание: This volume provides an overview of thefield of Hybrid Machine Translation (MT) and presents some of the latestresearch conducted by linguists and practitioners from differentmultidisciplinary areas. Nowadays, most important developments in MT are achievedby combining data-driven and rule-based techniques. These combinationstypically involve hybridization of different traditional paradigms, such as theintroduction of linguistic knowledge into statistical approaches to MT, theincorporation of data-driven components into rule-based approaches, orstatistical and rule-based pre- and post-processing for both types of MTarchitectures.The book is of interest primarily to MTspecialists, but also – in the wider fields of Computational Linguistics,Machine Learning and Data Mining – to translators and managers of translationcompanies and departments who are interested in recent developments concerningautomated translation tools.

Machine Translation

Автор: Muyun Yang; Shujie Liu
Название: Machine Translation
ISBN: 9811036349 ISBN-13(EAN): 9789811036347
Издательство: Springer
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Цена: 55890.00 T
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Описание: This book constitutes the refereed proceedings of the 12th China Workshop on Machine Translation, CWMT 2016, held in Urumqi, China, in August 2016. The 10 English papers presented in this volume were carefully reviewed and selected from 76 submissions.

Statistical machine translation

Автор: Koehn, Philipp
Название: Statistical machine translation
ISBN: 0521874157 ISBN-13(EAN): 9780521874151
Издательство: Cambridge Academ
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Цена: 69690.00 T
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Описание: Automatic language translation systems like those used by Google, have been revolutionized by recent advances in the methods used in statistical machine translation. This first textbook on the topic explains these innovations carefully and shows the reader, whether a student or a developer, how to build their own translation system.

Linguistic Issues in Machine Translation

Автор: Frank Van Eynde
Название: Linguistic Issues in Machine Translation
ISBN: 1474246540 ISBN-13(EAN): 9781474246545
Издательство: Bloomsbury Academic
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Цена: 147840.00 T
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Описание: The key assumption in this text is that machine translation is not merely a mechanical process but in fact requires a high level of linguistic sophistication, as the nuances of syntax, semantics and intonation cannot always be conveyed by modern technology. The increasing dependence on artificial communication by private and corporate users makes this research area an invaluable element when teaching linguistic theory.

Turning text into gold

Автор: Inmon, Bill
Название: Turning text into gold
ISBN: 1634621662 ISBN-13(EAN): 9781634621663
Издательство: Gazelle Book Services
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Цена: 37170.00 T
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Описание: In our distant past, we attempted to create wealth by turning everyday substances into gold. This was early alchemy, and ultimately it did not work. But the world has changed. Today we have a type of modern alchemy that really can create gold. We can transform voluminous text into a wealth of knowledge. Text is a common fabric of society, yet it is still challenging for our technology to make sense of text. This is where taxonomies can help. In this book, legendary Bill Inmon will introduce you to the concept of taxonomies and how they are used to simplify and understand text. We emphasise the practical aspects of taxonomies, and the subsequent usage of taxonomies as a basis for textual analytics. This book is for managers who have to deal with text, students of computer science, programmers who need to understand taxonomies, systems analysts who hope to draw business value out of a body of text, and especially those who are struggling to decode data lakes. Hopefully for those individuals (and many more), this book will serve as both an introduction to taxonomies and a guide to how taxonomies can be used to bring text into the realm of corporate decision-making. This book will introduce you to the world of taxonomies, as well as explore: Simple and complex taxonomies; Ontologies; Obtaining taxonomies; Changing taxonomies; Taxonomies and data models; Types of textual data; Textual analytics. In addition, several case studies are presented from industries as diverse as banking, call centres, and travel.

Learning machine translation

Название: Learning machine translation
ISBN: 0262072971 ISBN-13(EAN): 9780262072977
Издательство: MIT Press
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Цена: 11390.00 T
Наличие на складе: Нет в наличии.
Описание: The Internet gives us access to a wealth of information in languages we don`t understand. The investigation of automated or semi-automated approaches to translation has become a thriving research field with enormous commercial potential. This title investigates how Machine Learning techniques can improve Statistical Machine Translation.

Computer Age Statistical Inference

Автор: Bradley Efron and Trevor Hastie
Название: Computer Age Statistical Inference
ISBN: 1107149894 ISBN-13(EAN): 9781107149892
Издательство: Cambridge Academ
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Цена: 60190.00 T
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Описание: The twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and in influence. 'Big data', 'data science', and 'machine learning' have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science and commerce. How did we get here? And where are we going? This book takes us on an exhilarating journey through the revolution in data analysis following the introduction of electronic computation in the 1950s. Beginning with classical inferential theories - Bayesian, frequentist, Fisherian - individual chapters take up a series of influential topics: survival analysis, logistic regression, empirical Bayes, the jackknife and bootstrap, random forests, neural networks, Markov chain Monte Carlo, inference after model selection, and dozens more. The distinctly modern approach integrates methodology and algorithms with statistical inference. The book ends with speculation on the future direction of statistics and data science.


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