Серия "Synthesis Lectures on Human Language Technologies"

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Bayesian Analysis in Natural Langua...

Shay Cohen

Bayesian Analysis in Natural Language Processing

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Shay Cohen

Linguistic Fundamentals for Natural...

Emily M. Bender

Linguistic Fundamentals for Natural Language Processing II

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Meaning is a fundamental concept in Natural Language Processing (NLP), in the tasks of both Natural Language Understanding (NLU) and Natural Language Generation (NLG). This is because the aims of these fields are to build systems that understand what people mean when they speak or write, and that can produce linguistic strings that successfully express to people the intended content. In order for NLP to scale beyond partial, task-specific solutions, researchers in these fields must be informed...

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Emily M. Bender

Introduction to Chinese Natural Lan...

Ruifeng Xu

Introduction to Chinese Natural Language Processing

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Ruifeng Xu

Cross-Lingual Word Embeddings

Anders Søgaard

Cross-Lingual Word Embeddings

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Anders Søgaard

Recognizing Textual Entailment

Ido Dagan

Recognizing Textual Entailment

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In the last few years, a number of NLP researchers have developed and participated in the task of Recognizing Textual Entailment (RTE). This task encapsulates Natural Language Understanding capabilities within a very simple interface: recognizing when the meaning of a text snippet is contained in the meaning of a second piece of text. This simple abstraction of an exceedingly complex problem has broad appeal partly because it can be conceived also as a component in other NLP applications, from...

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Ido Dagan

Neural Network Methods in Natural L...

Yoav Goldberg

Neural Network Methods in Natural Language Processing

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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...

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Yoav Goldberg

Sentiment Analysis and Opinion Mini...

Bing Liu

Sentiment Analysis and Opinion Mining

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Sentiment analysis and opinion mining is the field of study that analyzes people's opinions, sentiments, evaluations, attitudes, and emotions from written language. It is one of the most active research areas in natural language processing and is also widely studied in data mining, Web mining, and text mining. In fact, this research has spread outside of computer science to the management sciences and social sciences due to its importance to business and society as a whole. The growing...

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Bing Liu

Quality Estimation for Machine Tran...

Lucia Specia

Quality Estimation for Machine Translation

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Lucia Specia

Argumentation Mining

Manfred Stede

Argumentation Mining

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Manfred Stede

Automatic Text Simplification

Horacio Saggion

Automatic Text Simplification

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Thanks to the availability of texts on the Web in recent years, increased knowledge and information have been made available to broader audiences. However, the way in which a text is written—its vocabulary, its syntax—can be difficult to read and understand for many people, especially those with poor literacy, cognitive or linguistic impairment, or those with limited knowledge of the language of the text. Texts containing uncommon words or longand complicated sentences can be difficult to read...

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Horacio Saggion

Domain-Sensitive Temporal Tagging

Jannik Strötgen

Domain-Sensitive Temporal Tagging

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This book covers the topic of temporal tagging, the detection of temporal expressions and the normalization of their semantics to some standard format. It places a special focus on the challenges and opportunities of domain-sensitive temporal tagging. After providing background knowledge on the concept of time, the book continues with a comprehensive survey of current research on temporal tagging. The authors provide an overview of existing techniques and tools, and highlight key issues that...

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Jannik Strötgen

Syntax-based Statistical Machine Tr...

Philip Williams

Syntax-based Statistical Machine Translation

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Philip Williams

Metaphor

Tony Veale

Metaphor

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The literary imagination may take flight on the wings of metaphor, but hard-headed scientists are just as likely as doe-eyed poets to reach for a metaphor when the descriptive need arises. Metaphor is a pervasive aspect of every genre of text and every register of speech, and is as useful for describing the inner workings of a «black hole» (itself a metaphor) as it is the affairs of the human heart. The ubiquity of metaphor in natural language thus poses a significant challenge for Natural...

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Tony Veale

Automatic Detection of Verbal Decep...

Eileen Fitzpatrick

Automatic Detection of Verbal Deception

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Eileen Fitzpatrick

Linked Lexical Knowledge Bases

Iryna Gurevych

Linked Lexical Knowledge Bases

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This book conveys the fundamentals of Linked Lexical Knowledge Bases (LLKB) and sheds light on their different aspects from various perspectives, focusing on their construction and use in natural language processing (NLP). It characterizes a wide range of both expert-based and collaboratively constructed lexical knowledge bases. Only basic familiarity with NLP is required and this book has been written for both students and researchers in NLP and related fields who are interested in...

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Iryna Gurevych

Semantic Similarity from Natural La...

Sébastien Harispe

Semantic Similarity from Natural Language and Ontology Analysis

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Sébastien Harispe

Semantic Relations Between Nominals

Vivi Nastase

Semantic Relations Between Nominals

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Vivi Nastase

Automated Grammatical Error Detecti...

Claudia Leacock

Automated Grammatical Error Detection for Language Learners

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Claudia Leacock

Statistical Language Models for Inf...

Chengxiang Zhai

Statistical Language Models for Information Retrieval

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Chengxiang Zhai

Computational Modeling of Narrative

Inderjeet Mani

Computational Modeling of Narrative

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Inderjeet Mani

Discourse Processing

Manfred Stede

Discourse Processing

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Manfred Stede

Web Corpus Construction

Roland Schäfer

Web Corpus Construction

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Roland Schäfer

Data-Intensive Text Processing with...

Jimmy Lin

Data-Intensive Text Processing with MapReduce

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Our world is being revolutionized by data-driven methods: access to large amounts of data has generated new insights and opened exciting new opportunities in commerce, science, and computing applications. Processing the enormous quantities of data necessary for these advances requires large clusters, making distributed computing paradigms more crucial than ever. MapReduce is a programming model for expressing distributed computations on massive datasets and an execution framework for large-scale...

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Jimmy Lin

Learning to Rank for Information Re...

Hang Li

Learning to Rank for Information Retrieval and Natural Language Processing

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Hang Li

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