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Algebraic Structures in Natural Language
Algebraic Structures in Natural Language addresses a central problem in cognitive science concerning the learning procedures through which humans acquire and represent natural language. Until recently algebraic systems have dominated the study of natural language in formal and computational linguistics, AI, and the psychology of language, with linguistic knowledge seen as encoded in formal grammars, model theories, proof theories and other rule-driven devices. Recent work on deep learning has produced an increasingly powerful set of general learning mechanisms which do not apply rule-based algebraic models of representation. The success of deep learning in NLP has led some researchers to que...
Multilingual Digital Humanities
Multilingual Digital Humanities explores the impact of monolingualism—especially Anglocentrism—on digital practices in the humanities and social sciences. The volume explores a wide range of applied contexts, such as digital linguistic injustice, critical digital literacy, digital learning, digital publishing, low-resourced, minoritised or endangered languages in a digital space, and multilingual historical intertextuality. These discussions are situated within wider work on language technologies, language documentation and international (in particular European) language-based infrastructure creation. Drawing on both primary and secondary research, this four-part book features 13 diverse...
Bioengineering and Biomedical Signal and Image Processing
This book constitutes the refereed proceedings of the First International Conference on Bioengineering and Biomedical Signal and Image Processing, BIOMESIP 2021, held in Meloneras, Gran Canaria, Spain, in July 2021. The 41 full and 5 short papers were carefully reviewed and selected from 121 submissions. The papers are grouped in topical issues on biomedical applications in molecular, structural, and functional imaging; biomedical computing; biomedical signal measurement, acquisition and processing; computerized medical imaging and graphics; disease control and diagnosis; neuroimaging; pattern recognition and machine learning for biosignal data; personalized medicine; and COVID-19.
ECAI 2023
Artificial intelligence, or AI, now affects the day-to-day life of almost everyone on the planet, and continues to be a perennial hot topic in the news. This book presents the proceedings of ECAI 2023, the 26th European Conference on Artificial Intelligence, and of PAIS 2023, the 12th Conference on Prestigious Applications of Intelligent Systems, held from 30 September to 4 October 2023 and on 3 October 2023 respectively in Kraków, Poland. Since 1974, ECAI has been the premier venue for presenting AI research in Europe, and this annual conference has become the place for researchers and practitioners of AI to discuss the latest trends and challenges in all subfields of AI, and to demonstrat...
Analysis of Images, Social Networks and Texts
This book constitutes the proceedings of the 7th International Conference on Analysis of Images, Social Networks and Texts, AIST 2018, held in Moscow, Russia, in July 2018. The 29 full papers were carefully reviewed and selected from 107 submissions (of which 26 papers were rejected without being reviewed). The papers are organized in topical sections on natural language processing; analysis of images and video; general topics of data analysis; analysis of dynamic behavior through event data; optimization problems on graphs and network structures; and innovative systems.
Text, Speech and Dialogue
This book constitutes the refereed proceedings of the 15th International Conference on Text, Speech and Dialogue, TSD 2012, held in Brno, Czech Republic, in September 2012. The 82 papers presented together with 2 invited talks were carefully reviewed and selected from 173 submissions. The papers are organized in topical sections on corpora and language resources, speech recognition, tagging, classification and parsing of text and speech, speech and spoken language generation, semantic processing of text and speech, integrating applications of text and speech processing, machine translation, automatic dialogue systems, multimodal techniques and modeling.
Natural Language Processing and Information Systems
This book constitutes the refereed proceedings of the 17th International Conference on Applications of Natural Language to Information Systems, held in Groningen, The Netherlands, in June 2012. The 12 full papers, 24 short papers and 16 poster papers presented in this volume together with a full-paper length invited talks were carefully reviewed and selected from 90 submissions. The rapidly evolving state-of-the-art in NLP and the shifting interest to appcliations targeting document and data collections available on the Web, including an increasing amount of user generated content, is reflected in the contributions to this book. Topics covered are information retrieval, text classification and clustering, summarization, normalization of user generated content, "forensic" NLP, ontologies and natural language, sentiment analysis, question answering and information extraction, terminology and named entity recognition, and NLP tools development.
Large Language Models
Large Language Models (LLMs) have emerged as a cornerstone technology, transforming how we interact with information and redefining the boundaries of artificial intelligence. LLMs offer an unprecedented ability to understand, generate, and interact with human language in an intuitive and insightful manner, leading to transformative applications across domains like content creation, chatbots, search engines, and research tools. While fascinating, the complex workings of LLMs -- their intricate architecture, underlying algorithms, and ethical considerations -- require thorough exploration, creating a need for a comprehensive book on this subject. This book provides an authoritative exploration...
Models of Modals
Modal verbs in English communicate delicate shades of meaning, there being a large range of verbs both on the necessity side (must, have to, should, ought to, need, need to) and the possibility side (can, may, could, might, be able to). They therefore constitute excellent test ground to apply and compare different methodologies that can lay bare the factors that drive the speaker’s choice of modal verb. This book is not merely concerned with a purely grammatical description of the use of modal verbs, but aims at advancing our understanding of lexical and grammatical units in general and of linguistic methodologies to explore these. It thus involves a genuine effort to compare, assess and c...
Explainable Natural Language Processing
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. The book is intended to provide a snapshot of Explainable NLP, though the field continues to rapidly grow. The book is intended to be both readable by first-year M.Sc. students and interesting to an expert audience. The book opens by motivating a focus on providing a consistent taxonomy, pointing out inconsistencies and redundancies in previous taxonomies. It goes on to present (i) a taxonomy or framework for thinking about how approaches to explainable NLP relate to one another; (ii) brief surveys of each of the classes in the taxonomy, with a focus on methods that are relevant for NLP; and (iii) a discussion of the inherent limitations of some classes of methods, as well as how to best evaluate them. Finally, the book closes by providing a list of resources for further research on explainability.
