Download or read book Management and Processing of Complex Data Structures written by Kai V. Luck and published by . This book was released on 2014-09-01 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Management and Processing of Complex Data Structures written by Kai von Luck and published by Springer Science & Business Media. This book was released on 1994-02-16 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume presents the proceedings of the third workshop on Information Systems and Artificial Intelligence, organized by the German Computer Science Society. The 11 invited contributions by well known researchers and developers working in the fields of databases and knowledge representation systems are centered around the topic of management and processing of complex data structures; they give a representative snapshot of the state-of-the-art in this fruitful interdisciplinary research area important for further progress in both, information systems and artificial intelligence. Most of the papers stress the demands for new or extended formalisms and their deductive capabilities, including an analysis of their formal properties for managing complex structures.
Download or read book Processing and Managing Complex Data for Decision Support written by Darmont, Jrme and published by IGI Global. This book was released on 2006-03-31 with total page 433 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book provides an overall view of the emerging field of complex data processing, highlighting the similarities between the different data, issues and approaches"--Provided by publisher.
Download or read book Management and Processing of Complex Data Structures written by and published by . This book was released on 1994 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Handbook of Data Structures and Applications written by Dinesh P. Mehta and published by Taylor & Francis. This book was released on 2018-02-21 with total page 1120 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Handbook of Data Structures and Applications was first published over a decade ago. This second edition aims to update the first by focusing on areas of research in data structures that have seen significant progress. While the discipline of data structures has not matured as rapidly as other areas of computer science, the book aims to update those areas that have seen advances. Retaining the seven-part structure of the first edition, the handbook begins with a review of introductory material, followed by a discussion of well-known classes of data structures, Priority Queues, Dictionary Structures, and Multidimensional structures. The editors next analyze miscellaneous data structures, which are well-known structures that elude easy classification. The book then addresses mechanisms and tools that were developed to facilitate the use of data structures in real programs. It concludes with an examination of the applications of data structures. Four new chapters have been added on Bloom Filters, Binary Decision Diagrams, Data Structures for Cheminformatics, and Data Structures for Big Data Stores, and updates have been made to other chapters that appeared in the first edition. The Handbook is invaluable for suggesting new ideas for research in data structures, and for revealing application contexts in which they can be deployed. Practitioners devising algorithms will gain insight into organizing data, allowing them to solve algorithmic problems more efficiently.
Download or read book Data Stream Management written by Minos Garofalakis and published by Springer. This book was released on 2016-07-11 with total page 537 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume focuses on the theory and practice of data stream management, and the novel challenges this emerging domain poses for data-management algorithms, systems, and applications. The collection of chapters, contributed by authorities in the field, offers a comprehensive introduction to both the algorithmic/theoretical foundations of data streams, as well as the streaming systems and applications built in different domains. A short introductory chapter provides a brief summary of some basic data streaming concepts and models, and discusses the key elements of a generic stream query processing architecture. Subsequently, Part I focuses on basic streaming algorithms for some key analytics functions (e.g., quantiles, norms, join aggregates, heavy hitters) over streaming data. Part II then examines important techniques for basic stream mining tasks (e.g., clustering, classification, frequent itemsets). Part III discusses a number of advanced topics on stream processing algorithms, and Part IV focuses on system and language aspects of data stream processing with surveys of influential system prototypes and language designs. Part V then presents some representative applications of streaming techniques in different domains (e.g., network management, financial analytics). Finally, the volume concludes with an overview of current data streaming products and new application domains (e.g. cloud computing, big data analytics, and complex event processing), and a discussion of future directions in this exciting field. The book provides a comprehensive overview of core concepts and technological foundations, as well as various systems and applications, and is of particular interest to students, lecturers and researchers in the area of data stream management.
Download or read book NBS Special Publication written by and published by . This book was released on 1976 with total page 780 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Algorithms and Data Structures for Massive Datasets written by Dzejla Medjedovic and published by Simon and Schuster. This book was released on 2022-08-16 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt: Massive modern datasets make traditional data structures and algorithms grind to a halt. This fun and practical guide introduces cutting-edge techniques that can reliably handle even the largest distributed datasets. In Algorithms and Data Structures for Massive Datasets you will learn: Probabilistic sketching data structures for practical problems Choosing the right database engine for your application Evaluating and designing efficient on-disk data structures and algorithms Understanding the algorithmic trade-offs involved in massive-scale systems Deriving basic statistics from streaming data Correctly sampling streaming data Computing percentiles with limited space resources Algorithms and Data Structures for Massive Datasets reveals a toolbox of new methods that are perfect for handling modern big data applications. You’ll explore the novel data structures and algorithms that underpin Google, Facebook, and other enterprise applications that work with truly massive amounts of data. These effective techniques can be applied to any discipline, from finance to text analysis. Graphics, illustrations, and hands-on industry examples make complex ideas practical to implement in your projects—and there’s no mathematical proofs to puzzle over. Work through this one-of-a-kind guide, and you’ll find the sweet spot of saving space without sacrificing your data’s accuracy. About the technology Standard algorithms and data structures may become slow—or fail altogether—when applied to large distributed datasets. Choosing algorithms designed for big data saves time, increases accuracy, and reduces processing cost. This unique book distills cutting-edge research papers into practical techniques for sketching, streaming, and organizing massive datasets on-disk and in the cloud. About the book Algorithms and Data Structures for Massive Datasets introduces processing and analytics techniques for large distributed data. Packed with industry stories and entertaining illustrations, this friendly guide makes even complex concepts easy to understand. You’ll explore real-world examples as you learn to map powerful algorithms like Bloom filters, Count-min sketch, HyperLogLog, and LSM-trees to your own use cases. What's inside Probabilistic sketching data structures Choosing the right database engine Designing efficient on-disk data structures and algorithms Algorithmic tradeoffs in massive-scale systems Computing percentiles with limited space resources About the reader Examples in Python, R, and pseudocode. About the author Dzejla Medjedovic earned her PhD in the Applied Algorithms Lab at Stony Brook University, New York. Emin Tahirovic earned his PhD in biostatistics from University of Pennsylvania. Illustrator Ines Dedovic earned her PhD at the Institute for Imaging and Computer Vision at RWTH Aachen University, Germany. Table of Contents 1 Introduction PART 1 HASH-BASED SKETCHES 2 Review of hash tables and modern hashing 3 Approximate membership: Bloom and quotient filters 4 Frequency estimation and count-min sketch 5 Cardinality estimation and HyperLogLog PART 2 REAL-TIME ANALYTICS 6 Streaming data: Bringing everything together 7 Sampling from data streams 8 Approximate quantiles on data streams PART 3 DATA STRUCTURES FOR DATABASES AND EXTERNAL MEMORY ALGORITHMS 9 Introducing the external memory model 10 Data structures for databases: B-trees, Bε-trees, and LSM-trees 11 External memory sorting
Download or read book Management written by and published by . This book was released on 1987 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Frontiers in Massive Data Analysis written by National Research Council and published by National Academies Press. This book was released on 2013-09-03 with total page 191 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data mining of massive data sets is transforming the way we think about crisis response, marketing, entertainment, cybersecurity and national intelligence. Collections of documents, images, videos, and networks are being thought of not merely as bit strings to be stored, indexed, and retrieved, but as potential sources of discovery and knowledge, requiring sophisticated analysis techniques that go far beyond classical indexing and keyword counting, aiming to find relational and semantic interpretations of the phenomena underlying the data. Frontiers in Massive Data Analysis examines the frontier of analyzing massive amounts of data, whether in a static database or streaming through a system. Data at that scale-terabytes and petabytes-is increasingly common in science (e.g., particle physics, remote sensing, genomics), Internet commerce, business analytics, national security, communications, and elsewhere. The tools that work to infer knowledge from data at smaller scales do not necessarily work, or work well, at such massive scale. New tools, skills, and approaches are necessary, and this report identifies many of them, plus promising research directions to explore. Frontiers in Massive Data Analysis discusses pitfalls in trying to infer knowledge from massive data, and it characterizes seven major classes of computation that are common in the analysis of massive data. Overall, this report illustrates the cross-disciplinary knowledge-from computer science, statistics, machine learning, and application disciplines-that must be brought to bear to make useful inferences from massive data.
Download or read book Software Engineering written by Bharat Bhushan Agarwal and published by Laxmi Publications. This book was released on 2009 with total page 273 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Database and Data Communication Network Systems Three Volume Set written by Cornelius T. Leondes and published by Academic Press. This book was released on 2002-07-02 with total page 1009 pages. Available in PDF, EPUB and Kindle. Book excerpt: Database and Data Communication Network Systems examines the utilization of the Internet and Local Area/Wide Area Networks in all areas of human endeavor. This three-volume set covers, among other topics, database systems, data compression, database architecture, data acquisition, asynchronous transfer mode (ATM) and the practical application of these technologies. The international collection of contributors was culled from exhaustive research of over 100,000 related archival and technical journals. This reference will be indispensable to engineering and computer science libraries, research libraries, and telecommunications, networking, and computer companies. It covers a diverse array of topics, including: * Techniques in emerging database system architectures * Techniques and applications in data mining * Object-oriented database systems * Data acquisition on the WWW during heavy client/server traffic periods * Information exploration on the WWW * Education and training in multimedia database systems * Data structure techniques in rapid prototyping and manufacturing * Wireless ATM in data networks for mobile systems * Applications in corporate finance * Scientific data visualization * Data compression and information retrieval * Techniques in medical systems, intensive care units
Download or read book Arihant CBSE Computer Science Term 2 Class 12 for 2022 Exam Cover Theory and MCQs written by Sanjib Pal and published by Arihant Publications India limited. This book was released on 2021-11-20 with total page 120 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the newly introduced 2 Term Examination Pattern, CBSE has eased out the pressure of preparation of subjects and cope up with lengthy syllabus. Introducing Arihant's CBSE TERM II – 2022 Series, the first of its kind that gives complete emphasis on the rationalized syllabus of Class 9th to 12th. The all new “CBSE Term II 2022 – Computer Science” of Class 12th provides explanation and guidance to the syllabus required to study efficiently and succeed in the exams. The book provides topical coverage of all the chapters in a complete and comprehensive manner. Covering the 50% of syllabus as per Latest Term wise pattern 2021-22, this book consists of: 1. Complete Theory in each Chapter covering all topics 2. Case-Based, Short and Long Answer Type Question in each chapter 3. Coverage of NCERT, NCERT Examplar & Board Exams’ Questions 4. Complete and Detailed explanations for each question 5. 3 Practice papers based on the entire Term II Syllabus. Table of Content Data Structures, Computer Networks and Web Services, Database Concepts, Structured and Query Language, Interface Python with SQL, Practice Papers (1-3).
Download or read book Application of Big Data Blockchain and Internet of Things for Education Informatization written by Yinjun Zhang and published by Springer Nature. This book was released on with total page 539 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Real Time Stream Data Management written by Wolfram Wingerath and published by Springer. This book was released on 2019-01-02 with total page 77 pages. Available in PDF, EPUB and Kindle. Book excerpt: While traditional databases excel at complex queries over historical data, they are inherently pull-based and therefore ill-equipped to push new information to clients. Systems for data stream management and processing, on the other hand, are natively pushoriented and thus facilitate reactive behavior. However, they do not retain data indefinitely and are therefore not able to answer historical queries. The book provides an overview over the different (push-based) mechanisms for data retrieval in each system class and the semantic differences between them. It also provides a comprehensive overview over the current state of the art in real-time databases. It sfirst includes an in-depth system survey of today's real-time databases: Firebase, Meteor, RethinkDB, Parse, Baqend, and others. Second, the high-level classification scheme illustrated above provides a gentle introduction into the system space of data management: Abstracting from the extreme system diversity in this field, it helps readers build a mental model of the available options.
Download or read book Global ocean science report written by UNESCO and published by UNESCO Publishing. This book was released on 2017-07-04 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Global Ocean Science Report (GOSR) assesses for the first time the status and trends in ocean science capacity around the world. The report offers a global record of how, where, and by whom ocean science is conducted: generating knowledge, helping to protect ocean health, and empowering society to support sustainable ocean management in the framework of the United Nations 2030 Agenda. The GOSR identifies and quantifies the key elements of ocean science at the national, regional and global scales, including workforce, infrastructure and publications. It is the first collective attempt to systematically highlight opportunities as well as capacity gaps to advance international collaboration in ocean science and technology. This report is a resource for policy-makers, academics and other stakeholders seeking to harness the potential of ocean science to address global challenges. A comprehensive view of ocean science capacities at the national and global levels takes us closer to developing the global ocean science knowledge needed to ensure a healthy, sustainable ocean.
Download or read book Classification and Multivariate Analysis for Complex Data Structures written by Bernard Fichet and published by Springer Science & Business Media. This book was released on 2011-03-04 with total page 460 pages. Available in PDF, EPUB and Kindle. Book excerpt: The growing capabilities in generating and collecting data has risen an urgent need of new techniques and tools in order to analyze, classify and summarize statistical information, as well as to discover and characterize trends, and to automatically bag anomalies. This volume provides the latest advances in data analysis methods for multidimensional data which can present a complex structure: The book offers a selection of papers presented at the first Joint Meeting of the Société Francophone de Classification and the Classification and Data Analysis Group of the Italian Statistical Society. Special attention is paid to new methodological contributions from both the theoretical and the applicative point of views, in the fields of Clustering, Classification, Time Series Analysis, Multidimensional Data Analysis, Knowledge Discovery from Large Datasets, Spatial Statistics.
