Серия "Synthesis Lectures on Human Language Technologies"

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Web Corpus Construction

Roland Schäfer

Web Corpus Construction

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Roland Schäfer

Syntax-based Statistical Machine Tr...

Philip Williams

Syntax-based Statistical Machine Translation

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Philip Williams

Statistical Significance Testing fo...

Rotem Dror

Statistical Significance Testing for Natural Language Processing

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Rotem Dror

Statistical Significance Testing fo...

Rotem Dror

Statistical Significance Testing for Natural Language Processing

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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...

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Rotem Dror

Statistical Language Models for Inf...

Chengxiang Zhai

Statistical Language Models for Information Retrieval

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Chengxiang Zhai

Spoken Dialogue Systems

Kristina Jokinen

Spoken Dialogue Systems

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Kristina Jokinen

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

Semi-Supervised Learning and Domain...

Anders Søgaard

Semi-Supervised Learning and Domain Adaptation in Natural Language Processing

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Anders Søgaard

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

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

Quality Estimation for Machine Tran...

Lucia Specia

Quality Estimation for Machine Translation

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Lucia Specia

Ontology-Based Interpretation of Na...

Christina Unger

Ontology-Based Interpretation of Natural Language

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Christina Unger

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

Natural Language Processing for Soc...

Diana Inkpen

Natural Language Processing for Social Media

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Diana Inkpen

Natural Language Processing for Soc...

Diana Inkpen

Natural Language Processing for Social Media

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In recent years, online social networking has revolutionized interpersonal communication. The newer research on language analysis in social media has been increasingly focusing on the latter's impact on our daily lives, both on a personal and a professional level. Natural language processing (NLP) is one of the most promising avenues for social media data processing. It is a scientific challenge to develop powerful methods and algorithms that extract relevant information from a large...

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Diana Inkpen

Natural Language Processing for His...

Michael Piotrowski

Natural Language Processing for Historical Texts

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Michael Piotrowski

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

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

Linguistic Structure Prediction

Noah A. Smith

Linguistic Structure Prediction

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Noah A. Smith

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