Natural language and machine translation

This book constitutes the refereed proceedings of the 4th International Workshop on Explainable and Transparent AI and Multi-Agent Systems, EXTRAAMAS 2022, held virtually during May 9-10, 2022.

Edited in collaboration with FoLLI, the Association of Logic, Language and Information this book constitutes the refereed proceedings of the 28th Workshop on Logic, Language, Information and Computation, WoLLIC 2022, Iasi, Romania, in September 2022.

This book constitutes the refereed proceedings of the 13th International Conference of the CLEF Association, CLEF 2022, held in Bologna, Italy in September 2022.

This book constitutes the proceedings of the 16th International Conference on Theoretical Aspects of Software Engineering, TASE 2022, held in Cluj-Napoca, Romania, July 2022.

This book includes chapters which discuss effective and efficient approaches in dealing with various aspects of social media analysis by using machine learning techniques from clustering to deep learning.

This book constitutes the proceedings of the 26th International Conference on Implementation and Application of Automata, CIAA 2022, held in Rouen, France in June/ July 2022.

This book constitutes the thoroughly refereed post-workshop proceedings of the 22nd Chinese Lexical Semantics Workshop, CLSW 2021, held in Nanjing, China in May 2021.

This book constitutes the proceedings of the 26th International Conference on Developments in Language Theory, DLT 2022, which was held in Tampa, FL, USA, during May, 2022.

Labelling data is one of the most fundamental activities in science, and has underpinned practice, particularly in medicine, for decades, as well as research in corpus linguistics since at least the development of the Brown corpus.

This book constitutes the refereed proceedings of the 9th Language and Technology Conference: Challenges for Computer Science and Linguistics, LTC 2019, held in Poznan, Poland, in May 2019.

Empirical methods are means to answering methodological questions of empirical sciences by statistical techniques.

This book discusses the state of the art of automated essay scoring, its challenges and its potential.

The goal of text ranking is to generate an ordered list of texts retrieved from a corpus in response to a query.

This book presents a taxonomy framework and survey of methods relevant to explaining the decisions and analyzing the inner workings of Natural Language Processing (NLP) models.

Weighted finite-state transducers (WFSTs) are commonly used by engineers and computational linguists for processing and generating speech and text.

Embeddings have undoubtedly been one of the most influential research areas in Natural Language Processing (NLP).

This book provides a comprehensive introduction to Conversational AI.

In recent years, online social networking has revolutionized interpersonal communication.

Data-driven experimental analysis has become the main evaluation tool of Natural Language Processing (NLP) algorithms.

Text production has many applications.

Meaning is a fundamental concept in Natural Language Processing (NLP), in the tasks of both Natural Language Understanding (NLU) and Natural Language Generation (NLG).

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.

Natural language processing (NLP) went through a profound transformation in the mid-1980s when it shifted to make heavy use of corpora and data-driven techniques to analyze language.

Many applications within natural language processing involve performing text-to-text transformations, i.

Thanks to the availability of texts on the Web in recent years, increased knowledge and information have been made available to broader audiences.

Opportunity and Curiosity find similar rocks on Mars.

Argumentation mining is an application of natural language processing (NLP) that emerged a few years ago and has recently enjoyed considerable popularity, as demonstrated by a series of international workshops and by a rising number of publications at the major conferences and journals of the field.

In recent years, online social networking has revolutionized interpersonal communication.

Neural networks are a family of powerful machine learning models.

This unique book provides a comprehensive introduction to the most popular syntax-based statistical machine translation models, filling a gap in the current literature for researchers and developers in human language technologies.

This book covers the topic of temporal tagging, the detection of temporal expressions and the normalization of their semantics to some standard format.

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.

This book provides a thorough introduction to the subfield of theoretical computer science known as grammatical inference from a computational linguistic perspective.

The attempt to spot deception through its correlates in human behavior has a long history.

It has been estimated that over a billion people are using or learning English as a second or foreign language, and the numbers are growing not only for English but for other languages as well.

The World Wide Web constitutes the largest existing source of texts written in a great variety of languages.

In the last few years, a number of NLP researchers have developed and participated in the task of Recognizing Textual Entailment (RTE).

Many NLP tasks have at their core a subtask of extracting the dependencies-who did what to whom-from natural language sentences.

This book introduces basic supervised learning algorithms applicable to natural language processing (NLP) and shows how the performance of these algorithms can often be improved by exploiting the marginal distribution of large amounts of unlabeled data.

People make sense of a text by identifying the semantic relations which connect the entities or concepts described by that text.

More and more historical texts are becoming available in digital form.

Discourse Processing here is framed as marking up a text with structural descriptions on several levels, which can serve to support many language-processing or text-mining tasks.

A major part of natural language processing now depends on the use of text data to build linguistic analyzers.

This book provides an overview of various techniques for the alignment of bitexts.

This book provides system developers and researchers in natural language processing and computational linguistics with the necessary background information for working with the Arabic language.

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.

This book is aimed at providing an overview of several aspects of semantic role labeling.

Considerable progress has been made in recent years in the development of dialogue systems that support robust and efficient human-machine interaction using spoken language.

This book introduces Chinese language-processing issues and techniques to readers who already have a basic background in natural language processing (NLP).

Linguistic annotation and text analytics are active areas of research and development, with academic conferences and industry events such as the Linguistic Annotation Workshops and the annual Text Analytics Summits.