Across numerous industries in modern society, there is a constant need to gather precise and relevant data efficiently and quickly. As such, it is imperative to research new methods and approaches to increase productivity in these areas. Ontologies and Big Data Considerations for Effective Intelligence is a key source on the latest advancements in multidisciplinary research methods and applications and examines effective techniques for managing and utilizing information resources. Featuring extensive coverage across a range of relevant perspectives and topics, such as visual analytics, spatial databases, retrieval systems, and ontology models, this book is ideally designed for researchers, graduate students, academics, and industry professionals seeking ways to optimize knowledge management processes.

Society is now completely driven by data with many industries relying on data to conduct business or basic functions within the organization. With the efficiencies that big data bring to all institutions, data is continuously being collected and analyzed. However, data sets may be too complex for traditional data-processing, and therefore, different strategies must evolve to solve the issue. The field of big data works as a valuable tool for many different industries. The Research Anthology on Big Data Analytics, Architectures, and Applications is a complete reference source on big data analytics that offers the latest, innovative architectures and frameworks and explores a variety of applications within various industries. Offering an international perspective, the applications discussed within this anthology feature global representation. Covering topics such as advertising curricula, driven supply chain, and smart cities, this research anthology is ideal for data scientists, data analysts, computer engineers, software engineers, technologists, government officials, managers, CEOs, professors, graduate students, researchers, and academicians.

Big data and machine learning are driving the Fourth Industrial Revolution. With the age of big data upon us, we risk drowning in a flood of digital data. Big data has now become a critical part of both the business world and daily life, as the synthesis and synergy of machine learning and big data has enormous potential. Big data and machine learning are projected to not only maximize citizen wealth, but also promote societal health. As big data continues to evolve and the demand for professionals in the field increases, access to the most current information about the concepts, issues, trends, and technologies in this interdisciplinary area is needed. The Encyclopedia of Data Science and Machine Learning examines current, state-of-the-art research in the areas of data science, machine learning, data mining, and more. It provides an international forum for experts within these fields to advance the knowledge and practice in all facets of big data and machine learning, emphasizing emerging theories, principals, models, processes, and applications to inspire and circulate innovative findings into research, business, and communities. Covering topics such as benefit management, recommendation system analysis, and global software development, this expansive reference provides a dynamic resource for data scientists, data analysts, computer scientists, technical managers, corporate executives, students and educators of higher education, government officials, researchers, and academicians.

For any organization to be successful, it must operate in such a manner that knowledge and information, human resources, and technology are continually taken into consideration and managed effectively. Business concepts are always present regardless of the field or industry – in education, government, healthcare, not-for-profit, engineering, hospitality/tourism, among others. Maintaining organizational awareness and a strategic frame of mind is critical to meeting goals, gaining competitive advantage, and ultimately ensuring sustainability. The Encyclopedia of Organizational Knowledge, Administration, and Technology is an inaugural five-volume publication that offers 193 completely new and previously unpublished articles authored by leading experts on the latest concepts, issues, challenges, innovations, and opportunities covering all aspects of modern organizations. Moreover, it is comprised of content that highlights major breakthroughs, discoveries, and authoritative research results as they pertain to all aspects of organizational growth and development including methodologies that can help companies thrive and analytical tools that assess an organization’s internal health and performance. Insights are offered in key topics such as organizational structure, strategic leadership, information technology management, and business analytics, among others. The knowledge compiled in this publication is designed for entrepreneurs, managers, executives, investors, economic analysts, computer engineers, software programmers, human resource departments, and other industry professionals seeking to understand the latest tools to emerge from this field and who are looking to incorporate them in their practice. Additionally, academicians, researchers, and students in fields that include but are not limited to business, management science, organizational development, entrepreneurship, sociology, corporate psychology, computer science, and information technology will benefit from the research compiled within this publication.

This book highlights recent research results in Bio-Inspired Computing and Applications. It presents 33 selected papers from the 8th International Conference on Innovations in Bio-Inspired Computing and Applications (IBICA 2017), which was held in Marrakesh, Morocco from December 11 to 13, 2017. A premier conference in the nature-inspired computing field, IBICA is intended to bring together the world’s leading researchers and practitioners interested in advancing the state of the art in biologically inspired computing, allowing them to exchange notes on a broad range of disciplines. The book offers a valuable reference guide for all researchers, students and practitioners in the fields of Computer Science and Engineering.

This two volume set of LNCS 11029 and LNCS 11030 constitutes the refereed proceedings of the 29th International Conference on Database and Expert Systems Applications, DEXA 2018, held in Regensburg, Germany, in September 2018. The 35 revised full papers presented together with 40 short papers were carefully reviewed and selected from 160 submissions. The papers of the first volume discuss a range of topics including: Big data analytics; data integrity and privacy; decision support systems; data semantics; cloud data processing; time series data; social networks; temporal and spatial databases; and graph data and road networks. The papers of the second volume discuss a range of the following topics: Information retrieval; uncertain information; data warehouses and recommender systems; data streams; information networks and algorithms; database system architecture and performance; novel database solutions; graph querying and databases; learning; emerging applications; data mining; privacy; and text processing.

Location-aware computing is a technology that uses the location (provides granular geographical information) of people and objects to derive contextual information. Today, one can obtain this location information free of cost through smartphones. Smartphones with location enabled applications have revolutionized the ways in which people perform their activities and get benefits from the automated services. It especially helps to get details of services in less time; wherever the user may be and whenever they want. The need for smartphones and location enabled applications has been growing year after year. Nowadays no one can leave without their phone; the phone seemingly becomes one of the parts of the human body. The individual can now be predicted by their phone and the identity of the phone becomes the person’s identity. Though there is a tremendous need for location-enabled applications with smartphones, the debate on privacy and security related to location data has also been growing. Privacy and Security Challenges in Location Aware Computing provides the latest research on privacy enhanced location-based applications development and exposes the necessity of location privacy preservation, as well as issues and challenges related to protecting the location data. It also suggests solutions for enhancing the protection of location privacy and therefore users’ privacy as well. The chapters highlight important topic areas such as video surveillance in human tracking/detection, geographical information system design, cyberspace attacks and warfare, and location aware security systems. The culmination of these topics creates a book that is ideal for security analysts, mobile application developers, practitioners, academicians, students, and researchers.