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Big Data Recommender Systems ; Vol.2 : Application Paradigms
Combines experimental and theoretical research on big data recommender systems to help computer scientists develop new concepts and methodologies for complex applications. It includes original scientific contributions in the form of theoretical foundations, comparative analysis, surveys, case studies, techniques and tools. First designed to generate personalized recommendations to users in the 90s, recommender systems apply knowledge discovery techniques to users’ data to suggest information, products, and services that best match their preferences. In recent decades, we have seen an exponential increase in the volumes of data, which has introduced many new challenges. recommender systems. Volume 2 covers a broad range of application paradigms for recommender systems over 22 chapters
Big Data Recommender Systems ; Vol.1 : Algorithms, Architectures, Big Data, Security and Trust
Combines experimental and theoretical research on big data recommender systems to help computer scientists develop new concepts and methodologies for complex applications. It includes original scientific contributions in the form of theoretical foundations, comparative analysis, surveys, case studies, techniques and tools.
Big Data Intelligence for Smart Applications
Presents the latest discoveries in the field of machine intelligence and big data Proposes many case studies and applications of computational and Big data Combines theory and practice so that readers of the few books (beginners or experts)
Big Data in Energy Economics
Combines energy economics and big data modeling analysis in energy conversion and management and comprehensively introduces the relevant theories, key technologies, and application examples of the smart energy economy. With the help of time series big data modeling results, energy economy managers develop reasonable and feasible pricing mechanisms of electricity price and improve the absorption capacity of the power grid. In addition, they also carry out scientific power equipment scheduling and cost–benefit analysis according to the results of data mining, so as to avoid the loss caused by accidental damage of equipment. Energy users adjust their power consumption behavior through the modeling results provided and achieve the effect of energy saving and emission reduction while reasonably reducing the electricity expenditure.
Big Data in Context : Legal, Social and Technological Insights
Sheds new light on a selection of big data scenarios from an interdisciplinary perspective. It features legal, sociological and economic approaches to fundamental big data topics such as privacy, data quality and the ECJ’s Safe Harbor decision on the one hand, and practical applications such as smart cars, wearables and web tracking on the other. Addressing the interests of researchers and practitioners alike, it provides a comprehensive overview of and introduction to the emerging challenges regarding big data.All contributions are based on papers submitted in connection with ABIDA (Assessing Big Data), an interdisciplinary research project exploring the societal aspects of big data and funded by the German Federal Ministry of Education and Research.
Big Data in Bioeconomy : Results from the European DataBio Project
This book presents the comprehensive outcome of The European DataBio Project, which examined new data-driven methods to shape a bioeconomy. These methods are used to develop new and sustainable ways to use forest, farm and fishery resources.
Big Data and Global Trade Law
Explores the relevance of global trade law for data, big data and cross-border data flows. Contributing authors from different disciplines including law, economics and political science analyze developments at the World Trade Organization and in preferential trade venues by asking what future-oriented models for data governance are available and viable in the area of trade law and policy. The collection paints the broad picture of the interaction between digital technologies and trade regulation as well as provides in-depth analyses of critical to the data-driven economy issues, such as privacy and AI, and different countries' perspectives.
Big data and artificial intelligence in digital finance : Increasing personalization and trust in digital finance using big data and AI
This book presents how cutting-edge digital technologies like Machine Learning, Artificial Intelligence (AI), and Blockchain are set to disrupt the financial sector. The book illustrates how recent advances in these technologies facilitate banks, FinTechs, and financial institutions to collect, process, analyze, and fully leverage the very large amounts of data that are nowadays produced and exchanged in the sector. To this end, the book also introduces some of the most popular Big Data, AI and Blockchain applications in the sector, including novel applications in the areas of Know Your Customer (KYC), Personalized Wealth Management and Asset Management, Portfolio Risk Assessment, as well as variety of novel Usage-based Insurance applications based on Internet-of-Things data.
Big data analytics and machine intelligence in biomedical and health informatics : Concepts, methodologies, tools and applications
Provides coverage of developments and state-of-the-art methods in the broad and diversified data analytics field and applicable areas such as big data analytics, data mining, and machine intelligence in biomedical and health informatics. Covers the latest advances and developments in health informatics, data mining, machine learning, and artificial intelligence. They have been organized with respect to the similarity of topics addressed, ranging from issues pertaining to the Internet of Things (IoT) for biomedical engineering and health informatics, computational intelligence for medical data processing, and Internet of Medical Things??(IoMT).
Big data analysis of nanoscience bibliometrics, patent, and funding data (2000-2019)
Presents an evaluation of nanotechnologies outputs (academic outputs and patents) and their impact from 2000-2019. The evaluation uses Elsevier’s Scopus (the largest abstract and citation database of peer-reviewed literature), SciVal (a scientific research analysis platform), Funding Institutional (a funding database), and PatentSight (a patent analysis platform). It covers four key topics regarding nanoscience research, including: 1) An overview of nano-related scholarly output, 2) Nanoscience and its contribution to basic science, 3) Nanoscience and its impact on and collaboration with industry partners, and 4) Key factors that promote the development of nanoscience.
Big Data : Conceptual Analysis and Applications
The book is devoted to the analysis of big data in order to extract from these data hidden patterns necessary for making decisions about the rational behavior of complex systems with the different nature that generate this data. To solve these problems, a group of new methods and tools is used, based on the self-organization of computational processes, the use of crisp and fuzzy cluster analysis methods, hybrid neural-fuzzy networks, and others. The book solves various practical problems. In particular, for the tasks of 3D image recognition and automatic speech recognition large-scale neural networks with applications for Deep Learning systems were used.
Big Data : An Art of Decision Making
Manipulating and processing masses of digital data is never a purely technical activity. It requires an interpretative and exploratory outlook - already well known in the social sciences and the humanities - to convey intelligible results from data analysis algorithms and create new knowledge. Big Data is based on an inquiry of several years within Proxem, a software publisher specializing in big data processing. The book examines how data scientists explore, interpret and visualize our digital traces to make sense of them, and to produce new knowledge. Grounded in epistemology and science and technology studies, Big Data offers a reflection on data in general, and on how they help us to better understand reality and decide on our daily actions.
Big Data : A Road Map for Successful Digital Marketing
Explores recent trends in the use of big data to predict consumer behavior, strategies to engage online customers, integration of big data with other data sources, and its applications in social media analytics, mobile marketing, search engine optimization and customer relationship management.
Big Data – BigData 2020; 9th International Conference, Held as Part of the Services Conference Federation, SCF 2020, Honolulu, HI, USA, September 18-20, 2020, Proceedings
Constitutes the proceedings of the 9th International Conference on Big Data, BigData 2020, held as part of SCF 2020, during September 18-20, 2020. The conference was planned to take place in Honolulu, HI, USA and was changed to a virtual format due to the COVID-19 pandemic. The 16 full and 3 short papers presented were carefully reviewed and selected from 52 submissions. The topics covered are Big Data Architecture, Big Data Modeling, Big Data As A Service, Big Data for Vertical Industries (Government, Healthcare, etc.), Big Data Analytics, Big Data Toolkits, Big Data Open Platforms, Economic Analysis, Big Data for Enterprise Transformation, Big Data in Business Performance Management, Big Data for Business Model Innovations and Analytics, Big Data in Enterprise Management Models and Practices, Big Data in Government Management Models and Practices, and Big Data in Smart Planet Solutions.
Beyond Cartesian Dualism : Encountering affect in the teaching and learning of science.
There is surprisingly little known about affect in science education. Despite periodic forays into monitoring students’ attitudes-toward-science, the effect of affect is too often overlooked. Beyond Cartesian Dualism gathers together contemporary theorizing in this axiomatic area. In fourteen chapters, senior scholars of international standing use their knowledge of the literature and empirical data to model the relationship between cognition and affect in science education. Their revealing discussions are grounded in a broad range of educational contexts including school classrooms, universities, science centres, travelling exhibits and refugee camps, and explore an array of far reaching questions. What is known about science teachers’ and students’ emotions? How do emotions mediate and moderate instruction? How might science education promote psychological
Between Mobility and Migration : The Multi-Level Governance of Intra-European Movement
Offers a critical perspective on intra-European mobility and migration by using new empirical data and theoretical discussions. It develops a theoretical and empirical analysis of the consequences of intra-European movement for sending and receiving urban regions in The Netherlands, Sweden, Austria, Turkey, Poland and Czech Republic.The book conceptualizes Central and Eastern European (CEE) migration by distinguishing between different types of CEE migrants and consequences. This involves a mapping of migration corridors within Europe, a unique empirical analysis of consequences for urban regions, and an analysis of governance responses. Next to the European and country perspectives on this phenomenon, the book focuses on the local perspective of urban regions where most mobile citizens settle (either permanently or temporarily). This way the book puts the analysis of intra-European movement in the perspective of broader theoretical debates in migration studies and beyond.
Between dirt and discussion : Methods, methodology and interpretation in historical archaeology
The cases presented in this volume revisit old methods and previous scholarly approaches with new perspectives, along with incorporating the newest technologies available to understanding the past.
Benchmarking, Temporal Distribution, and Reconciliation Methods for Time Series
This book discusses the statistical methods most often applied for such adjustments, ranging from ad hoc procedures to regression-based models. The latter are emphasized, because of their clarity, ease of application, and superior results. Each topic is illustrated with many real case examples. In order to facilitate understanding of their properties and limitations of the methods discussed, a real data example, the Canada Total Retail Trade Series, is followed throughout the book.This book brings together the scattered literature on these topics and presents them using a consistent notation and a unifying view.
Behavioral finance and your portfolio : A navigation guide for building wealth
Designed for investors who are serious about maximizing their gains, in this book you’ll discover how to: ● Take control of your decision-making—even when challenging markets push greed and fear to intolerable levels ● Reflect on how to make investment decisions using data-backed and substantiated information instead of emotion and bias ● Counter deep-seated biases like loss aversion, hindsight and overconfidence with self-awareness and hard facts ● Identify your personal investment psychology profile, which you can use to inform your future financial decision making
Behavioral competencies of digital professionals : Understanding the role of emotional intelligence
Shedding new light on the human side of big data through the lenses of emotional and social intelligence competencies, this book advances the understanding of the requirements of the different professions that deal with big data. It also illustrates the empirical evidence collected through the application of the competency-based methodology to a sample of data scientists and data analysts, the two most in-demand big data jobs in the labor market.
