Серия &quot;Synthesis Lectures on Human Language Technologies&quot;

Argumentation Mining

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Automated Grammatical Error Detecti...

Claudia Leacock

Automated Grammatical Error Detection for Language Learners

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Claudia Leacock

Automatic Detection of Verbal Decep...

Eileen Fitzpatrick

Automatic Detection of Verbal Deception

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Eileen Fitzpatrick

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

Bayesian Analysis in Natural Langua...

Shay Cohen

Bayesian Analysis in Natural Language Processing

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Shay Cohen

Bitext Alignment

Jörg Tiedemann

Bitext Alignment

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Jörg Tiedemann

Computational Modeling of Human Lan...

Afra Alishahi

Computational Modeling of Human Language Acquisition

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Afra Alishahi

Computational Modeling of Narrative

Inderjeet Mani

Computational Modeling of Narrative

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Inderjeet Mani

Cross-Language Information Retrieva...

Jian-Yun Nie

Cross-Language Information Retrieval

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Jian-Yun Nie

Cross-Lingual Word Embeddings

Anders Søgaard

Cross-Lingual Word Embeddings

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Anders Søgaard

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

Deep Learning Approaches to Text Pr...

Deep Learning Approaches to Text Production

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Text production has many applications. It is used, for instance, to generate dialogue turns from dialogue moves, verbalise the content of knowledge bases, or generate English sentences from rich linguistic representations, such as dependency trees or abstract meaning representations. Text production is also at work in text-to-text transformations such as sentence compression, sentence fusion, paraphrasing, sentence (or text) simplification, and text summarisation. This book offers an overview of...

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Deep Learning Approaches to Text Pr...

Deep Learning Approaches to Text Production

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Dependency Parsing

Sandra Kubler

Dependency Parsing

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Sandra Kubler

Discourse Processing

Discourse Processing

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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

Grammatical Inference for Computati...

Jeffrey Heinz

Grammatical Inference for Computational Linguistics

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Jeffrey Heinz

Introduction to Arabic Natural Lang...

Nizar Y. Habash

Introduction to Arabic Natural Language Processing

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Nizar Y. Habash

Introduction to Chinese Natural Lan...

Ruifeng Xu

Introduction to Chinese Natural Language Processing

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Ruifeng Xu

Introduction to Linguistic Annotati...

Graham Wilcock

Introduction to Linguistic Annotation and Text Analytics

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Graham Wilcock

Learning to Rank for Information Re...

Hang Li

Learning to Rank for Information Retrieval and Natural Language Processing

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Hang Li

Linguistic Fundamentals for Natural...

Linguistic Fundamentals for Natural Language Processing

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Linguistic Fundamentals for Natural...

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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