The last decade has seen a tremendous increase in the volume of data collected from personal and professional sources. While there have been many computational approaches available for analyzing these datasets, there is also growing interest in visualizing and making sense of spatio-temporal data. Geo-Intelligence and Visualization through Big Data Trends provides an overview of recent developments, applications, and research on the topic of spatio-temporal big data analysis and visualization, as well as location intelligence and analytics. Focusing on emerging trends in this dynamic field, this publication is an innovative resource aimed at the scholarly and professional interests of academicians, practitioners, and students.

The digital age has presented an exponential growth in the amount of data available to individuals looking to draw conclusions based on given or collected information across industries. Challenges associated with the analysis, security, sharing, storage, and visualization of large and complex data sets continue to plague data scientists and analysts alike as traditional data processing applications struggle to adequately manage big data. Big Data: Concepts, Methodologies, Tools, and Applications is a multi-volume compendium of research-based perspectives and solutions within the realm of large-scale and complex data sets. Taking a multidisciplinary approach, this publication presents exhaustive coverage of crucial topics in the field of big data including diverse applications, storage solutions, analysis techniques, and methods for searching and transferring large data sets, in addition to security issues. Emphasizing essential research in the field of data science, this publication is an ideal reference source for data analysts, IT professionals, researchers, and academics.

Having the ability to measure and explore the geographic space that surrounds us provides endless opportunities for us to utilize and interact with the world. As a broad field of study, geospatial research has applications in a variety of fields including military science, environmental science, civil engineering, and space exploration. Geospatial Research: Concepts, Methodologies, Tools, and Applications is a multi-volume publication highlighting critical topics related to geospatial analysis, geographic information systems, and geospatial technologies. Exploring multidisciplinary applications of geographic information systems and technologies in addition to the latest trends and developments in the field, this publication is ideal for academic and government library inclusion, as well as for reference by data scientists, engineers, government agencies, researchers, and graduate-level students in GIS programs.

The book presents a collection of peer-reviewed articles from the International Conference on Advances and Applications of Artificial Intelligence and Machine Learning—ICAAAIML 2021. The book covers research in the areas of artificial intelligence, machine learning, and deep learning applications in health care, agriculture, business, and security. This book contains research papers from academicians, researchers as well as students. There are also papers on core concepts of computer networks, intelligent system design and deployment, real-time systems, wireless sensor networks, sensors and sensor nodes, software engineering, and image processing. This book is a valuable resource for students, academics, and practitioners in the industry working on AI applications.

This book comprises theoretical foundations to deep learning, machine learning and computing system, deep learning algorithms, and various deep learning applications. The book discusses significant issues relating to deep learning in data analytics. Further in-depth reading can be done from the detailed bibliography presented at the end of each chapter. Besides, this book's material includes concepts, algorithms, figures, graphs, and tables in guiding researchers through deep learning in data science and its applications for society. Deep learning approaches prevent loss of information and hence enhance the performance of data analysis and learning techniques. It brings up many research issues in the industry and research community to capture and access data effectively. The book provides the conceptual basis of deep learning required to achieve in-depth knowledge in computer and data science. It has been done to make the book more flexible and to stimulate further interest in topics. All these help researchers motivate towards learning and implementing the concepts in real-life applications.

Geographic data is a valuable source of information in modern society. By utilizing alternative sources of this data, the availability and potential applications of geographic information systems can be increased. Volunteered Geographic Information and the Future of Geospatial Data is a pivotal reference source for the latest scholarly research on information gathering from volunteers, as opposed to official agencies and private companies, to compile geospatial data. Highlighting a range of pertinent topics such as regional landscape mapping, road safety, and land usage, this book is ideally designed for researchers, academics, students, professionals, and practitioners interested in the growing area of volunteered geographic information.

This book covers computationally innovative methods and technologies including data collection and elicitation, data processing, data analysis, data visualizations, and data presentation. It explores how digital humanists have harnessed the hypersociality and social technologies, benefited from the open-source sharing not only of data but of code, and made technological capabilities a critical part of humanities work. Chapters are written by researchers from around the world, bringing perspectives from diverse fields and subject areas. The respective authors describe their work, their research, and their learning. Topics include semantic web for cultural heritage valorization, machine learning for parody detection by classification, psychological text analysis, crowdsourcing imagery coding in natural disasters, and creating inheritable digital codebooks.Designed for researchers and academics, this book is suitable for those interested in methodologies and analytics that can be applied in literature, history, philosophy, linguistics, and related disciplines. Professionals such as librarians, archivists, and historians will also find the content informative and instructive.