This book constitutes the proceedings of the 25th International Workshop on Formal Methods for Industrial Critical Systems, FMICS 2020, which was held during September 2-3, 2020. The conference was planned to take place in Vienna, Austria. Due to the COVID-19 pandemic it changed to a virtual event.The 11 full papers presented in this volume were carefully reviewed and selected from 26 submissions. The papers are organized in topical sections as follows: Quantitative Analysis and Cyber-Physical Systems, Formal Verification of Industrial Systems, Temporal Logic and Model Checking. The book also contains a lengthy report on a Formal Methods Survey conducted on occasion of the 25th edition of the conference.

This volume celebrates the twentieth anniversary of CLEF - the Cross-Language Evaluation Forum for the first ten years, and the Conference and Labs of the Evaluation Forum since - and traces its evolution over these first two decades. CLEF's main mission is to promote research, innovation and development of information retrieval (IR) systems by anticipating trends in information management in order to stimulate advances in the field of IR system experimentation and evaluation. The book is divided into six parts. Parts I and II provide background and context, with the first part explaining what is meant by experimental evaluation and the underlying theory, and describing how this has been interpreted in CLEF and in other internationally recognized evaluation initiatives. Part II presents research architectures and infrastructures that have been developed to manage experimental data and to provide evaluation services in CLEF and elsewhere. Parts III, IV and V represent the core of the book, presenting some of the most significant evaluation activities in CLEF, ranging from the early multilingual text processing exercises to the later, more sophisticated experiments on multimodal collections in diverse genres and media. In all cases, the focus is not only on describing "what has been achieved", but above all on "what has been learnt". The final part examines the impact CLEF has had on the research world and discusses current and future challenges, both academic and industrial, including the relevance of IR benchmarking in industrial settings. Mainly intended for researchers in academia and industry, it also offers useful insights and tips for practitioners in industry working on the evaluation and performance issues of IR tools, and graduate students specializing in information retrieval.

This book constitutes the refereed proceedings of the 11th International Conference of the CLEF Association, CLEF 2020, held in Thessaloniki, Greece, in September 2020.*The conference has a clear focus on experimental information retrieval with special attention to the challenges of multimodality, multilinguality, and interactive search ranging from unstructured to semi structures and structured data. The 5 full papers and 2 short papers presented in this volume were carefully reviewed and selected from 9 submissions. This year, the contributions addressed the following challenges: a large-scale evaluation of translation effects in academic search, advancement of assessor-driven aggregation methods for efficient relevance assessments, and development of a new test dataset. In addition to this, the volume presents 7 "best of the labs" papers which were reviewed as full paper submissions with the same review criteria. The 12 lab overview papers were accepted out of 15 submissions and represent scientific challenges based on new data sets and real world problems in multimodal and multilingual information access. * The conference was held virtually due to the COVID-19 pandemic.

The book discusses subjective ratings of quality and preference of unknown voices and dialog partners - their likability, for example. Human natural and artificial voices are studied in passive listening and interactive scenarios. In this book, the background, state of research, and contributions to the assessment and prediction of talker quality that is constituted in voice perception and in dialog are presented. Starting from theories and empirical findings from human interaction, major results and approaches are transferred to the domain of human-computer interaction (HCI). The main objective of this book is to contribute to the evaluation of spoken interaction in humans and between humans and computers, and in particular to the quality subsequently attributed to the speaking system or person based on the listening and interactive experience. Provides a comprehensive overview of research in evaluation of speakers and dialog partners; Presents recent results on the relevance of a first passive and interactive impression; Includes human and HCI evaluation results from a communicative perspective.

This volume represents the first attempt in the field of language pedagogy to apply a systems approach to issues in English language education. In the literature of language education, or more specifically, second or foreign language learning and teaching, each topic or issue has often been dealt with independently, and been treated as an isolated item. Taking grammar instruction as an example, grammatical items are often taught in a sequential, step-by-step manner; there has been no "road map" in which the interrelations between the various items are demonstrated. This may be one factor that makes it more difficult for students to learn the language organically. The topics covered in this volume, including language acquisition, pedagogical grammar, and teacher collaboration, are viewed from a holistic perspective. In other words, language pedagogy is approached as a dynamic system of interrelations. In this way, "emergent properties" are expected to manifest. This book is recommended for anyone involved in language pedagogy, including researchers, teachers, and teacher trainers, as well as learners.

This book constitutes the refereed proceedings of the 34th IFIP TC 11 International Conference on Information Security and Privacy Protection, SEC 2019, held in Lisbon, Portugal, in June 2019. The 26 revised full papers presented were carefully reviewed and selected from 76 submissions. The papers present novel research on theoretical and practical aspects of security and privacy protection in ICT systems. They are organized in topical sections on intrusion detection, access control, organizational and behavioral, crypto and encryption, and integrity.

This publication explores how natural language processing (NLP) techniques can be applied to social media text data to map public sentiment and inform development research and policy making. The publication introduces the foundations of natural language analyses and showcases studies that have applied NLP techniques to make progress on the Sustainable Development Goals. It also reviews specific NLP techniques and concepts, supported by two case studies. The first case study analyzes public sentiments on the coronavirus disease (COVID-19) in the Philippines while the second case study explores the public debate on climate change in Australia.

This book constitutes the refereed proceedings of the 16th International Conference of the Pacific Association for Computational Linguistics, PACLING 2019, held in Hanoi, Vietnam, in October 2019. The 28 full papers and 14 short papers presented were carefully reviewed and selected from 70 submissions. The papers are organized in topical sections on text summarization; relation and word embedding; machine translation; text classification; web analyzing; question and answering, dialog analyzing; speech and emotion analyzing; parsing and segmentation; information extraction; and grammar error and plagiarism detection.

This book constitutes the refereed proceedings of the 5th International School on Engineering Trustworthy Software Systems, SETSS 2019, held in Chongqing, China, in April 2019. The five chapters in this volume provide lectures on leading-edge research in methods and tools for use in computer system engineering. The topics covered in these chapter include Seamless Model-based System Development: Foundations; From Bounded Reachability Analysis of Linear Hybrid Automata to Verification of Industrial CPS and IoT; Weakest Preexpectation Semantics for Bayesian Inference: Conditioning, Continuous Distributions and Divergence; K - A Semantic Framework for Programming Languages and Formal Analysis Tools; and Software Abstractions and Human-Cyber-Physical Systems Architecture Modelling.

We intend to edit a Festschrift for Henk Moed combining a "best of" collection of his papers and new contributions (original research papers) by authors having worked and collaborated with him. The outcome of this original combination aims to provide an overview of the advancement of the field in the intersection of bibliometrics, informetrics, science studies and research assessment.

This book constitutes the refereed proceedings of the 25th International Conference on Applications of Natural Language to Information Systems, NLDB 2020, held in Saarbrucken, Germany, in June 2020.* The 15 full papers and 10 short papers were carefully reviewed and selected from 68 submissions. The papers are organized in the following topical sections: semantic analysis; question answering and answer generation; classification; sentiment analysis; personality, affect and emotion; retrieval, conversational agents and multimodal analysis. *The conference was held virtually due to the COVID-19 pandemic.

This book constitutes the proceedings of the 24th International Conference on Developments in Language Theory, DLT 2020, which was due to be held in Tampa, Florida, USA, in May 2020. The conference was cancelled due to the COVID-19 pandemic. The 24 full papers presented were carefully reviewed and selected from 38 submissions. The papers present current developments in language theory, formal languages, automata theory and related areas, such as algorithmic, combinatorial, and algebraic properties of words and languages, cellular automata, algorithms on words, etc.

This book constitutes the refereed proceedings of the 17th International Semantic Web Conference, ESWC 2020, held in Heraklion, Crete, Greece.* The 39 revised full papers presented were carefully reviewed and selected from 166 submissions. The papers were submitted to three tracks: the research track, the resource track and the in-use track. These tracks showcase research and development activities, services and applications, and innovative research outcomes making their way into industry. The research track caters for both long standing and emerging research topics in the form of the following subtracks: ontologies and reasoning; natural language processing and information retrieval; semantic data management and data infrastructures; social and human aspects of the Semantic Web; machine learning; distribution and decentralization; science of science; security, privacy, licensing and trust; knowledge graphs; and integration, services and APIs. *The conference was held virtually due to the COVID-19 pandemic. Chapter 'Piveau: A Large-scale Oopen Data Management Platform based on Semantic Web Technologies' is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

This open access book constitutes the proceedings of the 29th European Symposium on Programming, ESOP 2020, which was planned to take place in Dublin, Ireland, in April 2020, as Part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2020. The actual ETAPS 2020 meeting was postponed due to the Corona pandemic. The papers deal with fundamental issues in the specification, design, analysis, and implementation of programming languages and systems.

Take your NLP knowledge to the next level by working with start-of-the-art transformer models and problem-solving real-world use cases, harnessing the strengths of Hugging Face, OpenAI, AllenNLP, and Google Trax Key Features Pretrain a BERT-based model from scratch using Hugging Face Fine-tune powerful transformer models, including OpenAI's GPT-3, to learn the logic of your data Perform root cause analysis on hard NLP problems Book DescriptionTransformers are...well...transforming the world of AI. There are many platforms and models out there, but which ones best suit your needs? Transformers for Natural Language Processing, 2nd Edition, guides you through the world of transformers, highlighting the strengths of different models and platforms, while teaching you the problem-solving skills you need to tackle model weaknesses. You'll use Hugging Face to pretrain a RoBERTa model from scratch, from building the dataset to defining the data collator to training the model. If you're looking to fine-tune a pretrained model, including GPT-3, then Transformers for Natural Language Processing, 2nd Edition, shows you how with step-by-step guides. The book investigates machine translations, speech-to-text, text-to-speech, question-answering, and many more NLP tasks. It provides techniques to solve hard language problems and may even help with fake news anxiety (read chapter 13 for more details). You'll see how cutting-edge platforms, such as OpenAI, have taken transformers beyond language into computer vision tasks and code creation using Codex. By the end of this book, you'll know how transformers work and how to implement them and resolve issues like an AI detective! What you will learn Find out how ViT and CLIP label images (including blurry ones!) and create images from a sentence using DALL-E Discover new techniques to investigate complex language problems Compare and contrast the results of GPT-3 against T5, GPT-2, and BERT-based transformers Carry out sentiment analysis, text summarization, casual speech analysis, machine translations, and more using TensorFlow, PyTorch, and GPT-3 Measure the productivity of key transformers to define their scope, potential, and limits in production Who this book is forIf you want to learn about and apply transformers to your natural language (and image) data, this book is for you. A good understanding of NLP, Python, and deep learning is required to benefit most from this book. Many platforms covered in this book provide interactive user interfaces, which allow readers with a general interest in NLP and AI to follow several chapters of this book.

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 a community, rely on empirical evaluation to validate our hypotheses and reveal the correct language processing mechanisms, we better be sure that our results are not coincidental. The goal of this book is to discuss the main aspects of statistical significance testing in NLP. Our guiding assumption throughout the book is that the basic question NLP researchers and engineers deal with is whether or not one algorithm can be considered better than another one. This question drives the field forward as it allows the constant progress of developing better technology for language processing challenges. In practice, researchers and engineers would like to draw the right conclusion from a limited set of experiments, and this conclusion should hold for other experiments with datasets they do not have at their disposal or that they cannot perform due to limited time and resources. The book hence discusses the opportunities and challenges in using statistical significance testing in NLP, from the point of view of experimental comparison between two algorithms. We cover topics such as choosing an appropriate significance test for the major NLP tasks, dealing with the unique aspects of significance testing for non-convex deep neural networks, accounting for a large number of comparisons between two NLP algorithms in a statistically valid manner (multiple hypothesis testing), and, finally, the unique challenges yielded by the nature of the data and practices of the field.

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 volume of data coming from multiple sources and languages in various formats or in free form. This book will discuss the challenges in analyzing social media texts in contrast with traditional documents. Research methods in information extraction, automatic categorization and clustering, automatic summarization and indexing, and statistical machine translation need to be adapted to a new kind of data. This book reviews the current research on NLP tools and methods for processing the non-traditional information from social media data that is available in large amounts, and it shows how innovative NLP approaches can integrate appropriate linguistic information in various fields such as social media monitoring, health care, and business intelligence. The book further covers the existing evaluation metrics for NLP and social media applications and the new efforts in evaluation campaigns or shared tasks on new datasets collected from social media. Such tasks are organized by the Association for Computational Linguistics (such as SemEval tasks), the National Institute of Standards and Technology via the Text REtrieval Conference (TREC) and the Text Analysis Conference (TAC), or the Conference and Labs of the Evaluation Forum (CLEF). In this third edition of the book, the authors added information about recent progress in NLP for social media applications, including more about the modern techniques provided by deep neural networks (DNNs) for modeling language and analyzing social media data.

This Festschrift is in honor of Chris Hankin, Professor at the Imperial College in London, UK, on the Occasion of His 65th Birthday.Chris Hankin is a Fellow of the Institute for Security Science and Technology and a Professor of Computing Science. His research is in cyber security, data analytics and semantics-based program analysis. He leads multidisciplinary projects focused on developing advanced visual analytics and providing better decision support to defend against cyber attacks. This Festschrift is a collection of scientific contributions related to the topics that have marked the research career of Professor Chris Hankin. The contributions have been written to honour Chris' career and on the occasion of his retirement.

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 the fundamentals of neural models for text production. In particular, we elaborate on three main aspects of neural approaches to text production: how sequential decoders learn to generate adequate text, how encoders learn to produce better input representations, and how neural generators account for task-specific objectives. Indeed, each text-production task raises a slightly different challenge (e.g, how to take the dialogue context into account when producing a dialogue turn, how to detect and merge relevant information when summarising a text, or how to produce a well-formed text that correctly captures the information contained in some input data in the case of data-to-text generation). We outline the constraints specific to some of these tasks and examine how existing neural models account for them. More generally, this book considers text-to-text, meaning-to-text, and data-to-text transformations. It aims to provide the audience with a basic knowledge of neural approaches to text production and a roadmap to get them started with the related work. The book is mainly targeted at researchers, graduate students, and industrials interested in text production from different forms of inputs.

This volume constitutes the refereed proceedings of the Confederated International International Workshop on Enterprise Integration, Interoperability and Networking (EI2N ), Fact Based Modeling ( FBM), Industry Case Studies Program ( ICSP ), International Workshop on Methods, Evaluation, Tools and Applications for the Creation and Consumption of Structured Data for the e-Society (Meta4eS) and, 1st International Workshop on Security via Information Analytics and Applications (SIAnA 2019) held as part of OTM 2018 in October 2019 in Rhodes, Greece. As the three main conferences and the associated workshops all share the distributed aspects of modern computing systems, they experience the application pull created by the Internet and by the so-called Semantic Web, in particular developments of Big Data, increased importance of security issues, and the globalization of mobile-based technologies.

This book constitutes the thoroughly refereed post conference papers of the First International Conference on Blockchain and Trustworthy Systems, Blocksys 2019, held in Guangzhou, China, in December 2019. The 50 regular papers and the 19 short papers were carefully reviewed and selected from 130 submissions. The papers are focus on Blockchain and trustworthy systems can be applied to many fields, such as financial services, social management and supply chain management.

This book constitutes the refereed proceedings of the Third International Workshop on Chatbot Research and Design, CONVERSATIONS 2019, held in Amsterdam, The Netherlands, in November 2019. The 18 revised full papers presented in this volume were carefully reviewed and selected from 31 submissions. The papers are grouped in the following topical sections: user and communication studies user experience and design, chatbots for collaboration, chatbots for customer service, and chatbots in education.

This book constitutes the thoroughly refereed proceedings of the 9th Joint International Semantic Technology Conference, JIST 2019, held in Hangzhou, China, in November 2019.The 12 full papers and 12 short papers presented were carefully reviewed and selected from 70 submissions. The papers present applications of semantic technologies, theoretical results, new algorithms and tools to facilitate the adoption of semantic technologies.

This book constitutes the refereed proceedings of the 13th International Conference, NooJ 2019, held in Hammamet, Tunisia, in June 2019. NooJ is a linguistic development environment that allows linguists to formalize several levels of linguistic phenomena. NooJ provides linguists with tools to develop dictionaries, regular grammars, context-free grammars, context-sensitive grammars and unrestricted grammars as well as their graphical equivalent to formalize each linguistic phenomenon. The 18 full papers presented were carefully reviewed and selected from 54 submissions. The papers are organized in the following tracks: Development of Linguistic Resources, Natural Language Processing Applications, NooJ for the Digital Humanities.

This book constitutes the thoroughly refereed proceedings of the 13th International Conference on Metadata and Semantic Research, MTSR 2019, held in Rome, Italy, in October 2019. The 27 full and 15 short papers presented were carefully reviewed and selected from 96 submissions. The papers are organized in the following tracks: metadata and semantics for digital libraries, information retrieval, big, linked, social and open data; metadata and semantics for agriculture, food, and environment; digital humanities and digital curation; cultural collections and applications; european and national projects; metadata, identifiers and semantics in decentralized applications, blockchains and P2P systems.