Download or read book Natural Language Processing in Artificial Intelligence NLPinAI 2020 written by Roussanka Loukanova and published by Springer Nature. This book was released on 2021-03-25 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers theoretical work, applications, approaches, and techniques for computational models of information and its presentation by language (artificial, human, or natural in other ways). Computational and technological developments that incorporate natural language are proliferating. Adequate coverage encounters difficult problems related to ambiguities and dependency on context and agents (humans or computational systems). The goal is to promote computational systems of intelligent natural language processing and related models of computation, language, thought, mental states, reasoning, and other cognitive processes.

Download or read book Natural Language Processing in Artificial Intelligence NLPinAI 2021 written by Roussanka Loukanova and published by Springer Nature. This book was released on 2021-11-01 with total page 126 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book covers theoretical work, approaches, applications, and techniques for computational models of information, language, and reasoning. Computational and technological developments that incorporate natural language are proliferating. Adequate coverage of natural language processing in artificial intelligence encounters problems on developments of specialized computational approaches and algorithms. Many difficulties are due to ambiguities in natural language and dependency of interpretations on contexts and agents. Classical approaches proceed with relevant updates, and new developments emerge in theories of formal and natural languages, computational models of information and reasoning, and related computerized applications. Its focus is on computational processing of human language and relevant medium languages, which can be theoretically formal, or for programming and specification of computational systems. The goal is to promote intelligent natural language processing, along with models of computation, language, reasoning, and other cognitive processes.

Download or read book Modelling Natural Language with Claude Shannon s Notion of Surprisal written by Michael Richter and published by Walter de Gruyter GmbH & Co KG. This book was released on 2024-02-19 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt: Have you ever wondered how the principles behind Shannon's groundbreaking Information Theory can be interwoven with the intricate fabric of linguistic communication? This book takes you on a fascinating journey, offering insights into how humans process and comprehend language. By applying Information Theory to the realm of natural language semantics, it unravels the connection between regularities in linguistic messages and the cognitive intricacies of language processing. Highlighting the intersections of information theory with linguistics, philosophy, cognitive psychology, and computer science, this book serves as an inspiration for anyone seeking to understand the predictive capabilities of Information Theory in modeling human communication. It elaborates on the seminal works from giants in the field like Dretske, Hale, and Zipf, exploring concepts like surprisal theory and the principle of least effort. With its empirical approach, this book not only discusses the theoretical aspects but also ventures into the application of Shannon's Information Theory in real-world language scenarios, strengthened by advanced statistical methods and machine learning. It touches upon challenging areas such as the distinction between mathematical and semantic information, the concept of information in linguistic utterances, and the intricate play between truth, context, and meaning. Whether you are a linguist, a cognitive psychologist, a philosopher, or simply an enthusiast eager to dive deep into the world where language meets information, this book promises a thought-provoking journey.

Download or read book Intelligent Computing written by Kohei Arai and published by Springer Nature. This book was released on 2022-07-06 with total page 941 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book, “Intelligent Computing - Proceedings of the 2022 Computing Conference”, is a comprehensive collection of chapters focusing on the core areas of computing and their further applications in the real world. Each chapter is a paper presented at the Computing Conference 2022 held on July 14–15, 2022. Computing 2022 attracted a total of 498 submissions which underwent a double-blind peer-review process. Of those 498 submissions, 179 submissions have been selected to be included in this book. The goal of this conference is to give a platform to researchers with fundamental contributions and to be a premier venue for academic and industry practitioners to share new ideas and development experiences. We hope that readers find this book interesting and valuable as it provides the state-of-the-art intelligent methods and techniques for solving real-world problems. We also expect that the conference and its publications will be a trigger for further related research and technology improvements in this important subject.

Download or read book Information structure and information theory written by Robin Lemke and published by Language Science Press. This book was released on 2024-09-19 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume results from the workshop "Discourse obligates – How and why discourse limits the way we express what we express" at the 44th Annual Meeting of the German Linguistic Society in Tübingen, Germany. The workshop brought - and this book brings - together information-structural and information-theoretic perspectives on optional variation between linguistic encodings. Previously, linguistic phenomena like linearization, the choice between syntactic constructions or the distribution of ellipsis have been investigated from an information-structural or information-theoretic perspective, but the relationship between these approaches remains underexplored. The goal of this book is to look more in detail into how information structure and information theory contribute to explaining linguistic variation, to what extent they explain different encoding choices and whether they interact in doing so. Using experimental and corpus-based methods, the contributions investigate this on different languages, historical stages and levels of linguistic analysis.

Download or read book Transparent Logics Small Differences with Huge Consequences written by Miloš Kosterec and published by BRILL. This book was released on 2024-08-01 with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book presents Transparent Intensional Logic in several of its latest realisations in such a way that it makes a case for the system and demonstrates how the theory can be applied to a wide range of cases. The work strikes a good balance between the philosophical-conceptual and the logical-formal. Transparent Logics prioritises depth over breadth and focuses on advanced formal semantics and philosophical logic, going beyond a mere introduction to the subject, but delving into the details instead.

Download or read book Information Modelling and Knowledge Bases XXXIV written by M. Tropmann-Frick and published by IOS Press. This book was released on 2023-02-07 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: The amount and complexity of information is continually growing, and information modeling and knowledge bases have become important contributors to technology and to academic and industrial research in the 21st century. They address the complexities of modeling in digital transformation and digital innovation, reaching beyond the traditional borders of information systems and academic computer-science research. This book presents the proceedings of EJC 2022, the 32nd International conference on Information Modeling and Knowledge Bases, held as a hybrid event due to restrictions related to the Corona virus pandemic in Hamburg, Germany, from 30 May to 3 June 2022. The aim of the conference is to bring together experts from different areas of computer science and other disciplines with a common interest in understanding and solving the problems of information modeling and knowledge bases and applying the results of research to practice. The conference has always been open to new topics related to its main themes, and the content emphasis of the conferences have changed through the years according to developments in the research field, so philosophy and logic, cognitive science, knowledge management, linguistics, and management science, as well as machine learning and AI, are also relevant areas. This book presents 19 reviewed and selected papers covering a wide range of topics, upgraded as a result of comments and discussions during the conference. Providing a current overview of recent developments, the book will be of interest to all those using information modeling and knowledge bases as part of their work.

Download or read book Multi Agent Systems written by Vadim Malvone and published by Springer Nature. This book was released on 2023-09-06 with total page 571 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume LNCS 14282 constitutes the refereed proceedings of the 20th European Conference EUMAS 2023, held in Naples, Italy, during September 2023. This volume includes 24 full papers and 5 short papers, carefully selected from 47 submissions. Additionally, the volume features 16 short papers, rigorously reviewed from 20 submissions for the PhD day. The conference focused on the theory and practice of autonomous agents and multi-agent systems, covering a wide range of topics.

Download or read book Logic and Algorithms in Computational Linguistics 2021 LACompLing2021 written by Roussanka Loukanova and published by Springer Nature. This book was released on 2023-03-11 with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book assesses the place of logic, mathematics, and computer science in present day, interdisciplinary areas of computational linguistics. Computational linguistics studies natural language in its various manifestations from a computational point of view, both on the theoretical level (modeling grammar modules dealing with natural language form and meaning and the relation between these two) and on the practical level (developing applications for language and speech technology). It is a collection of chapters presenting new and future research. The book focuses mainly on logical approaches to computational processing of natural language and on the applicability of methods and techniques from the study of formal languages, programming, and other specification languages. It presents work from other approaches to linguistics, as well, especially because they inspire new work and approaches.

Download or read book Data Management Technologies and Applications written by Alfredo Cuzzocrea and published by Springer Nature. This book was released on 2023-08-23 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed post-proceedings of the 10th International Conference and 11th International Conference on Data Management Technologies and Applications, DATA 2021 and DATA 2022, was held virtually due to the COVID-19 crisis on July 6–8, 2021 and in Lisbon, Portugal on July 11-13, 2022. The 11 full papers included in this book were carefully reviewed and selected from 148 submissions. They were organized in topical sections as follows: engineers and practitioners interested on databases, big data, data mining, data management, data security and other aspects of information systems and technology involving advanced applications of data.

Download or read book Light Verb Constructions as Complex Verbs written by Anna Pompei and published by Walter de Gruyter GmbH & Co KG. This book was released on 2023-10-23 with total page 378 pages. Available in PDF, EPUB and Kindle. Book excerpt: The notion of light verb constructions has been traditionally related to the ‘insignificance’ of the verb, which is described as a grammatical item only codifying TAM system and φ-features, whereas the whole predicative content is thought to be conveyed by the noun. This book deals with the light verb constructions as instances of complex verbs, intended as multi-predicational but monoclausal structures. This allows to deepen the actual verb lightness, the effective noun predicativity, as well as their effect on the cohesion of the construction. The papers in this volume reflect on the concrete contribution of noun and verb to the event and argument structure, and on the relevance of semantically different noun classes for the verb selection. From different theoretical approaches, data of a great variety of languages are investigated, such as Indo-European languages – both modern (Germanic, Slavic, Romance and Iranian languages) and ancient (Latin and Ancient Greek) – but also Mandarin Chinese, and different polysynthetic languages (e.g. Ket, Nivkh, Murrinh-Patha, Kiowa, Bininj Gun-wok, Ainu). The range of topics, languages and perspectives presented in this book make it of great interest to both theoretical and applied linguists.

Download or read book Natural Language Processing written by Raymond S. T. Lee and published by Springer Nature. This book was released on 2023-12-16 with total page 454 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook presents an up-to-date and comprehensive overview of Natural Language Processing (NLP), from basic concepts to core algorithms and key applications. Further, it contains seven step-by-step NLP workshops (total length: 14 hours) offering hands-on practice with essential Python tools like NLTK, spaCy, TensorFlow Kera, Transformer and BERT. The objective of this book is to provide readers with a fundamental grasp of NLP and its core technologies, and to enable them to build their own NLP applications (e.g. Chatbot systems) using Python-based NLP tools. It is both a textbook and NLP tool-book intended for the following readers: undergraduate students from various disciplines who want to learn NLP; lecturers and tutors who want to teach courses or tutorials for undergraduate/graduate students on NLP and related AI topics; and readers with various backgrounds who want to learn NLP, and more importantly, to build workable NLP applications after completing its 14 hours of Python-based workshops.

Download or read book Deep Learning for Natural Language Processing written by Karthiek Reddy Bokka and published by Packt Publishing Ltd. This book was released on 2019-06-11 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt: Gain the knowledge of various deep neural network architectures and their application areas to conquer your NLP issues. Key FeaturesGain insights into the basic building blocks of natural language processingLearn how to select the best deep neural network to solve your NLP problemsExplore convolutional and recurrent neural networks and long short-term memory networksBook Description Applying deep learning approaches to various NLP tasks can take your computational algorithms to a completely new level in terms of speed and accuracy. Deep Learning for Natural Language Processing starts off by highlighting the basic building blocks of the natural language processing domain. The book goes on to introduce the problems that you can solve using state-of-the-art neural network models. After this, delving into the various neural network architectures and their specific areas of application will help you to understand how to select the best model to suit your needs. As you advance through this deep learning book, you’ll study convolutional, recurrent, and recursive neural networks, in addition to covering long short-term memory networks (LSTM). Understanding these networks will help you to implement their models using Keras. In the later chapters, you will be able to develop a trigger word detection application using NLP techniques such as attention model and beam search. By the end of this book, you will not only have sound knowledge of natural language processing but also be able to select the best text pre-processing and neural network models to solve a number of NLP issues. What you will learnUnderstand various pre-processing techniques for deep learning problemsBuild a vector representation of text using word2vec and GloVeCreate a named entity recognizer and parts-of-speech tagger with Apache OpenNLPBuild a machine translation model in KerasDevelop a text generation application using LSTMBuild a trigger word detection application using an attention modelWho this book is for If you’re an aspiring data scientist looking for an introduction to deep learning in the NLP domain, this is just the book for you. Strong working knowledge of Python, linear algebra, and machine learning is a must.

Download or read book Natural Language Processing in Action written by Hannes Hapke and published by Simon and Schuster. This book was released on 2019-03-16 with total page 798 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary Natural Language Processing in Action is your guide to creating machines that understand human language using the power of Python with its ecosystem of packages dedicated to NLP and AI. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Recent advances in deep learning empower applications to understand text and speech with extreme accuracy. The result? Chatbots that can imitate real people, meaningful resume-to-job matches, superb predictive search, and automatically generated document summaries—all at a low cost. New techniques, along with accessible tools like Keras and TensorFlow, make professional-quality NLP easier than ever before. About the Book Natural Language Processing in Action is your guide to building machines that can read and interpret human language. In it, you'll use readily available Python packages to capture the meaning in text and react accordingly. The book expands traditional NLP approaches to include neural networks, modern deep learning algorithms, and generative techniques as you tackle real-world problems like extracting dates and names, composing text, and answering free-form questions. What's inside Some sentences in this book were written by NLP! Can you guess which ones? Working with Keras, TensorFlow, gensim, and scikit-learn Rule-based and data-based NLP Scalable pipelines About the Reader This book requires a basic understanding of deep learning and intermediate Python skills. About the Author Hobson Lane, Cole Howard, and Hannes Max Hapke are experienced NLP engineers who use these techniques in production. Table of Contents PART 1 - WORDY MACHINES Packets of thought (NLP overview) Build your vocabulary (word tokenization) Math with words (TF-IDF vectors) Finding meaning in word counts (semantic analysis) PART 2 - DEEPER LEARNING (NEURAL NETWORKS) Baby steps with neural networks (perceptrons and backpropagation) Reasoning with word vectors (Word2vec) Getting words in order with convolutional neural networks (CNNs) Loopy (recurrent) neural networks (RNNs) Improving retention with long short-term memory networks Sequence-to-sequence models and attention PART 3 - GETTING REAL (REAL-WORLD NLP CHALLENGES) Information extraction (named entity extraction and question answering) Getting chatty (dialog engines) Scaling up (optimization, parallelization, and batch processing)

Download or read book Natural Language Processing and Computational Linguistics written by Bhargav Srinivasa-Desikan and published by Packt Publishing Ltd. This book was released on 2018-06-29 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt: Work with Python and powerful open source tools such as Gensim and spaCy to perform modern text analysis, natural language processing, and computational linguistics algorithms. Key Features Discover the open source Python text analysis ecosystem, using spaCy, Gensim, scikit-learn, and Keras Hands-on text analysis with Python, featuring natural language processing and computational linguistics algorithms Learn deep learning techniques for text analysis Book Description Modern text analysis is now very accessible using Python and open source tools, so discover how you can now perform modern text analysis in this era of textual data. This book shows you how to use natural language processing, and computational linguistics algorithms, to make inferences and gain insights about data you have. These algorithms are based on statistical machine learning and artificial intelligence techniques. The tools to work with these algorithms are available to you right now - with Python, and tools like Gensim and spaCy. You'll start by learning about data cleaning, and then how to perform computational linguistics from first concepts. You're then ready to explore the more sophisticated areas of statistical NLP and deep learning using Python, with realistic language and text samples. You'll learn to tag, parse, and model text using the best tools. You'll gain hands-on knowledge of the best frameworks to use, and you'll know when to choose a tool like Gensim for topic models, and when to work with Keras for deep learning. This book balances theory and practical hands-on examples, so you can learn about and conduct your own natural language processing projects and computational linguistics. You'll discover the rich ecosystem of Python tools you have available to conduct NLP - and enter the interesting world of modern text analysis. What you will learn Why text analysis is important in our modern age Understand NLP terminology and get to know the Python tools and datasets Learn how to pre-process and clean textual data Convert textual data into vector space representations Using spaCy to process text Train your own NLP models for computational linguistics Use statistical learning and Topic Modeling algorithms for text, using Gensim and scikit-learn Employ deep learning techniques for text analysis using Keras Who this book is for This book is for you if you want to dive in, hands-first, into the interesting world of text analysis and NLP, and you're ready to work with the rich Python ecosystem of tools and datasets waiting for you!

Download or read book Natural Language Processing in Artificial Intelligence written by Brojo Kishore Mishra and published by CRC Press. This book was released on 2020-11-01 with total page 297 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume focuses on natural language processing, artificial intelligence, and allied areas. Natural language processing enables communication between people and computers and automatic translation to facilitate easy interaction with others around the world. This book discusses theoretical work and advanced applications, approaches, and techniques for computational models of information and how it is presented by language (artificial, human, or natural) in other ways. It looks at intelligent natural language processing and related models of thought, mental states, reasoning, and other cognitive processes. It explores the difficult problems and challenges related to partiality, underspecification, and context-dependency, which are signature features of information in nature and natural languages. Key features: Addresses the functional frameworks and workflow that are trending in NLP and AI Looks at the latest technologies and the major challenges, issues, and advances in NLP and AI Explores an intelligent field monitoring and automated system through AI with NLP and its implications for the real world Discusses data acquisition and presents a real-time case study with illustrations related to data-intensive technologies in AI and NLP.

Download or read book Deep Learning in Natural Language Processing written by Li Deng and published by Springer. This book was released on 2018-05-23 with total page 338 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years, deep learning has fundamentally changed the landscapes of a number of areas in artificial intelligence, including speech, vision, natural language, robotics, and game playing. In particular, the striking success of deep learning in a wide variety of natural language processing (NLP) applications has served as a benchmark for the advances in one of the most important tasks in artificial intelligence. This book reviews the state of the art of deep learning research and its successful applications to major NLP tasks, including speech recognition and understanding, dialogue systems, lexical analysis, parsing, knowledge graphs, machine translation, question answering, sentiment analysis, social computing, and natural language generation from images. Outlining and analyzing various research frontiers of NLP in the deep learning era, it features self-contained, comprehensive chapters written by leading researchers in the field. A glossary of technical terms and commonly used acronyms in the intersection of deep learning and NLP is also provided. The book appeals to advanced undergraduate and graduate students, post-doctoral researchers, lecturers and industrial researchers, as well as anyone interested in deep learning and natural language processing.