Computational Analysis And Understanding Of Natural Languages Principles Methods And Applications

Computational Analysis and Understanding of Natural Languages: Principles, Methods and Applications, Volume 38, the latest release in this monograph that provides a cohesive and integrated exposition of these advances and associated applications, includes new chapters on Linguistics: Core Concepts and Principles, Grammars, Open-Source Libraries, Application Frameworks, Workflow Systems, Mathematical Essentials, Probability, Inference and Prediction Methods, Random Processes, Bayesian Methods, Machine Learning, Artificial Neural Networks for Natural Language Processing, Information Retrieval, Language Core Tasks, Language Understanding Applications, and more. The synergistic confluence of linguistics, statistics, big data, and high-performance computing is the underlying force for the recent and dramatic advances in analyzing and understanding natural languages, hence making this series all the more important. Provides a thorough treatment of open-source libraries, application frameworks and workflow systems for natural language analysis and understanding Presents new chapters on Linguistics: Core Concepts and Principles, Grammars, Open-Source Libraries, Application Frameworks, Workflow Systems, Mathematical Essentials, Probability, and more

This book constitutes 5 revised tutorial lectures of the 9th European Business Intelligence and Big Data Summer School, eBISS 2019, held in Berlin, Germany, during June 30 – July 5, 2019. The tutorials were given by renowned experts and covered advanced aspects of business intelligence and big data. This summer school, presented by leading researchers in the field, represented an opportunity for postgraduate students to equip themselves with the theoretical and practical skills necessary for developing challenging business intelligence applications.

This comprehensive reference work provides an overview of the concepts, methodologies, and applications in computational linguistics and natural language processing (NLP). Features contributions by the top researchers in the field, reflecting the work that is driving the discipline forward Includes an introduction to the major theoretical issues in these fields, as well as the central engineering applications that the work has produced Presents the major developments in an accessible way, explaining the close connection between scientific understanding of the computational properties of natural language and the creation of effective language technologies Serves as an invaluable state-of-the-art reference source for computational linguists and software engineers developing NLP applications in industrial research and development labs of software companies

This book gathers selected papers presented at the 7th International Conference on Inventive Communication and Computational Technologies conference (ICICCT 2023), held on May 22–23, 2023, at Gnanamani College of Technology, Tamil Nadu, India. The book covers the topics such as Internet of things, social networks, mobile communications, big data analytics, bio-inspired computing and cloud computing. The book is exclusively intended for academics and practitioners working to resolve practical issues in this area.

This book presents the latest research, theoretical methods, and novel applications in the field of Health 5.0. The authors focus on combating COVID-19 or other pandemics through facilitating various technological services. The authors discuss new models, practical solutions, and technological advances related to detecting and analyzing COVID-19 or other pandemic based on machine intelligence models and communication technologies. The aim of the coverage is to help decision-makers, managers, professionals, and researchers design new paradigms considering the unique opportunities associated with computational intelligence and Internet of Medical Things (IoMT). This book emphasizes the need to analyze all the information through studies and research carried out in the field of computational intelligence, communication networks, and presents the best solutions to combat COVID and other pandemics.

The 3-volume set LNAI 13280, LNAI 13281 and LNAI 13282 constitutes the proceedings of the 26th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2022, which was held during May 2022 in Chengdu, China. The 121 papers included in the proceedings were carefully reviewed and selected from a total of 558 submissions. They were organized in topical sections as follows: Part I: Data Science and Big Data Technologies, Part II: Foundations; and Part III: Applications.

This book presents the creation of a bilingual thesaurus (Italian and English), and its conversion into an ontology system, oriented to the Cybersecurity field of knowledge term management and the identification of a replicable method over other specialized areas of study, through computational linguistics procedures, to a statistical and qualitative measurement of the terminological coverage threshold a controlled vocabulary is able to guarantee with respect to the semantic richness proper to the domain under investigation. The volume empowers readers to compile and study significant corpora documentations to support the text mining tasks and to establish a representativeness evaluation of the information retrieved. Through a description of several techniques belonging to the field of linguistics and knowledge engineering, this monograph provides a methodological account on how to enhance and update semantic monitoring tools reflecting a specialized lexicon as that of Cybersecurity to grant a reference semantic structure for domain-sector text classification tasks. This volume is a valuable reference to scholars of corpus-based studies, terminology, ICT, documentation and librarianship studies, text processing research, and distributional semantics area of interest as well as for professionals involved in Cybersecurity organizations.

In today's rapidly evolving world, the exponential growth of data poses a significant challenge. As data volumes increase, traditional methods of analysis and decision-making become inadequate. This surge in data complexity calls for innovative solutions that efficiently extract meaningful insights. Machine learning has emerged as a powerful tool to address this challenge, offering algorithms and techniques to analyze large datasets and uncover hidden patterns, trends, and correlations. Machine Learning Techniques and Industry Applications demystifies machine learning through detailed explanations, examples, and case studies, making it accessible to a broad audience. Whether you're a student, researcher, or practitioner, this book equips you with the knowledge and skills needed to harness the power of machine learning to address diverse challenges. From e-government to healthcare, cyber-physical systems to agriculture, this book explores how machine learning can drive innovation and sustainable development.