Автор: Ahmed Название: Big and Complex Data Analysis ISBN: 3319415727 ISBN-13(EAN): 9783319415727 Издательство: Springer Рейтинг: Цена: 102480.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This volume conveys some of the surprises, puzzles and success stories in high-dimensional and complex data analysis and related fields. Examples include epigenomic data, genomic data, proteomic data, high-resolution image data, high-frequency financial data, functional and longitudinal data, and network data.
Автор: Rabl Название: Big Data Benchmarking ISBN: 3319497472 ISBN-13(EAN): 9783319497471 Издательство: Springer Рейтинг: Цена: 39130.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book constitutes the thoroughly refereed post-workshop proceedings of the 6th International Workshop on Big Data Benchmarking, WBDB 2015, held in Toronto, ON, Canada, in June 2015 and the 7th International Workshop, WBDB 2015, held in New Delhi, India, in December 2015.
Автор: Angelov Название: Advances in Big Data ISBN: 3319478974 ISBN-13(EAN): 9783319478975 Издательство: Springer Рейтинг: Цена: 186330.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The book offers a timely snapshot of neural network technologies as a significant component of big data analytics platforms. It promotes new advances and research directions in efficient and innovative algorithmic approaches to analyzing big data (e.g. deep networks, nature-inspired and brain-inspired algorithms); implementations on different computing platforms (e.g. neuromorphic, graphics processing units (GPUs), clouds, clusters); and big data analytics applications to solve real-world problems (e.g. weather prediction, transportation, energy management). The book, which reports on the second edition of the INNS Conference on Big Data, held on October 23–25, 2016, in Thessaloniki, Greece, depicts an interesting collaborative adventure of neural networks with big data and other learning technologies.
Автор: Mahmood Название: Data Science and Big Data Computing ISBN: 3319318594 ISBN-13(EAN): 9783319318592 Издательство: Springer Рейтинг: Цена: 121110.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This illuminating text/reference surveys the state of the art in data science, and provides practical guidance on big data analytics. Expert perspectives are provided by authoritative researchers and practitioners from around the world, discussing research developments and emerging trends, presenting case studies on helpful frameworks and innovative methodologies, and suggesting best practices for efficient and effective data analytics. Features: reviews a framework for fast data applications, a technique for complex event processing, and agglomerative approaches for the partitioning of networks; introduces a unified approach to data modeling and management, and a distributed computing perspective on interfacing physical and cyber worlds; presents techniques for machine learning for big data, and identifying duplicate records in data repositories; examines enabling technologies and tools for data mining; proposes frameworks for data extraction, and adaptive decision making and social media analysis.
Автор: Paola Pucci; Fabio Manfredini; Paolo Tagliolato Название: Mapping Urban Practices Through Mobile Phone Data ISBN: 331914832X ISBN-13(EAN): 9783319148328 Издательство: Springer Рейтинг: Цена: 52240.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book explains the potential value of using mobile phone data to monitor urban practices and identify rhythms of use in today`s cities.
Автор: Ivan Название: The Rise of Big Spatial Data ISBN: 3319451227 ISBN-13(EAN): 9783319451220 Издательство: Springer Рейтинг: Цена: 204970.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This edited volume gathers the proceedings of the Symposium GIS Ostrava 2016, the Rise of Big Spatial Data, held at the Technical University of Ostrava, Czech Republic, March 16–18, 2016. Combining theoretical papers and applications by authors from around the globe, it summarises the latest research findings in the area of big spatial data and key problems related to its utilisation.Welcome to dawn of the big data era: though it’s in sight, it isn’t quite here yet. Big spatial data is characterised by three main features: volume beyond the limit of usual geo-processing, velocity higher than that available using conventional processes, and variety, combining more diverse geodata sources than usual. The popular term denotes a situation in which one or more of these key properties reaches a point at which traditional methods for geodata collection, storage, processing, control, analysis, modelling, validation and visualisation fail to provide effective solutions. >Entering the era of big spatial data calls for finding solutions that address all “small data” issues that soon create “big data” troubles. Resilience for big spatial data means solving the heterogeneity of spatial data sources (in topics, purpose, completeness, guarantee, licensing, coverage etc.), large volumes (from gigabytes to terabytes and more), undue complexity of geo-applications and systems (i.e. combination of standalone applications with web services, mobile platforms and sensor networks), neglected automation of geodata preparation (i.e. harmonisation, fusion), insufficient control of geodata collection and distribution processes (i.e. scarcity and poor quality of metadata and metadata systems), limited analytical tool capacity (i.e. domination of traditional causal-driven analysis), low visual system performance, inefficient knowledge-discovery techniques (for transformation of vast amounts of information into tiny and essential outputs) and much more. These trends are accelerating as sensors become more ubiquitous around the world.
Автор: Daim Название: Anticipating Future Innovation Pathways Through Large Data Analysis ISBN: 3319390546 ISBN-13(EAN): 9783319390543 Издательство: Springer Рейтинг: Цена: 107130.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book aims to identify promising future developmental opportunities and applications for Tech Mining. Specifically, the enclosed contributions will pursue three converging themes:The increasing availability of electronic text data resources relating to Science, Technology and Innovation (ST&I).The multiple methods that are able to treat this data effectively and incorporate means to tap into human expertise and interests.Translating those analyses to provide useful intelligence on likely future developments of particular emerging S&T targets. Tech Mining can be defined as text analyses of ST&I information resources to generate Competitive Technical Intelligence (CTI). It combines bibliometrics and advanced text analytic, drawing on specialized knowledge pertaining to ST&I. Tech Mining may also be viewed as a special form of “Big Data” analytics because it searches on a target emerging technology (or key organization) of interest in global databases. One then downloads, typically, thousands of field-structured text records (usually abstracts), and analyses those for useful CTI. Forecasting Innovation Pathways (FIP) is a methodology drawing on Tech Mining plus additional steps to elicit stakeholder and expert knowledge to link recent ST&I activity to likely future development. A decade ago, we demeaned Management of Technology (MOT) as somewhat self-satisfied and ignorant. Most technology managers relied overwhelmingly on casual human judgment, largely oblivious of the potential of empirical analyses to inform R&D management and science policy. CTI, Tech Mining, and FIP are changing that. The accumulation of Tech Mining research over the past decade offers a rich resource of means to get at emerging technology developments and organizational networks to date. Efforts to bridge from those recent histories of development to project likely FIP, however, prove considerably harder. One focus of this volume is to extend the repertoire of information resources; that will enrich FIP.Featuring cases of novel approaches and applications of Tech Mining and FIP, this volume will present frontier advances in ST&I text analytics that will be of interest to students, researchers, practitioners, scholars and policy makers in the fields of R&D planning, technology management, science policy and innovation strategy.
Автор: Amin Ash Название: Seeing Like a City ISBN: 0745664261 ISBN-13(EAN): 9780745664262 Издательство: Wiley Рейтинг: Цена: 17940.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Seeing like a city means recognizing that cities are living things made up of a tangle of networks, built up from the agency of countless actors. Cities must not be considered as expressions of larger paradigms or sites of human effort and organization alone.
Автор: Mittelstadt Название: The Ethics of Biomedical Big Data ISBN: 3319335235 ISBN-13(EAN): 9783319335230 Издательство: Springer Рейтинг: Цена: 107130.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book presents cutting edge research on the new ethical challenges posed by biomedical Big Data technologies and practices. ‘Biomedical Big Data’ refers to the analysis of aggregated, very large datasets to improve medical knowledge and clinical care. The book describes the ethical problems posed by aggregation of biomedical datasets and re-use/re-purposing of data, in areas such as privacy, consent, professionalism, power relationships, and ethical governance of Big Data platforms. Approaches and methods are discussed that can be used to address these problems to achieve the appropriate balance between the social goods of biomedical Big Data research and the safety and privacy of individuals. Seventeen original contributions analyse the ethical, social and related policy implications of the analysis and curation of biomedical Big Data, written by leading experts in the areas of biomedical research, medical and technology ethics, privacy, governance and data protection. The book advances our understanding of the ethical conundrums posed by biomedical Big Data, and shows how practitioners and policy-makers can address these issues going forward.
Автор: Roos Название: Understanding Relational and Group Experiences through the Mmogo-Method® ISBN: 3319312227 ISBN-13(EAN): 9783319312224 Издательство: Springer Рейтинг: Цена: 83850.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This volume describes the development and application of the Mmogo-method® as a projective visual data-gathering method, applied in different contexts and with different groups of people. 'Mmogo' means togetherness in Setswana, one of the 11 official languages of South Africa. The Mmogo-method® provides a deep understanding of personal, relational and group experiences and is particularly useful in cross-cultural contexts and across age groups. By allowing visual expressions of the self as a complex, dynamic social system it overcomes some of the limitations of traditional data-collection methods, such as questionnaires or interviews. The book draws together contributions by leading social scientists to show how this flexible, visual data-collection method can be used independently or jointly with other data-gathering techniques, such as journalling or in-depth interviewing, to acquire rich information. The research method described here enables investigators to access perceptions, feelings and personal experiences participants might otherwise find hard to verbalize and explain. Researchers in disciplines such as education, social sciences, consumer sciences, market research, and city and town planning will find this book and its innovative method particularly valuable in addressing a gap in available visual and other data collection resources.
Автор: Usman Название: Improving Knowledge Discovery Through The Integration Of Data Mining Techniques ISBN: 1466685131 ISBN-13(EAN): 9781466685130 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 218990.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Data warehousing is an important topic that is of interest to both the industry and the knowledge engineering research communities. Both data mining and data warehousing technologies have similar objectives and can potentially benefit from each other’s methods to facilitate knowledge discovery.Improving Knowledge Discovery through the Integration of Data Mining Techniques provides insight concerning the integration of data mining and data warehousing for enhancing the knowledge discovery process. Decision makers, academicians, researchers, advanced-level students, technology developers, and business intelligence professionals will find this book useful in furthering their research exposure to relevant topics in knowledge discovery.
Автор: Lau John Название: Through-Silicon Vias for 3D Integration ISBN: 0071785140 ISBN-13(EAN): 9780071785143 Издательство: McGraw-Hill Рейтинг: Цена: 184170.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This professional book focuses on the latest cost- and space-saving methods of 3D integrated circuits-essential for the development of low-cost, high-performance electronic and optoelectronic products.
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