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Author: Stanisław Kozielski
Publisher: Springer
ISBN: 3319340999
Category : Computers
Languages : en
Pages : 744
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Book Description
This book constitutes the refereed proceedings of the 12th International Conference entitled Beyond Databases, Architectures and Structures, BDAS 2016, held in Ustroń, Poland, in May/June 2016. It consists of 57 carefully reviewed papers selected from 152 submissions. The papers are organized in topical sections, namely artificial intelligence, data mining and knowledge discovery; architectures, structures and algorithms for efficient data processing; data warehousing and OLAP; natural language processing, ontologies and semantic Web; bioinformatics and biomedical data analysis; data processing tools; novel applications of database systems.
Author: Stanisław Kozielski
Publisher: Springer
ISBN: 3319340999
Category : Computers
Languages : en
Pages : 744
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Book Description
This book constitutes the refereed proceedings of the 12th International Conference entitled Beyond Databases, Architectures and Structures, BDAS 2016, held in Ustroń, Poland, in May/June 2016. It consists of 57 carefully reviewed papers selected from 152 submissions. The papers are organized in topical sections, namely artificial intelligence, data mining and knowledge discovery; architectures, structures and algorithms for efficient data processing; data warehousing and OLAP; natural language processing, ontologies and semantic Web; bioinformatics and biomedical data analysis; data processing tools; novel applications of database systems.
Author: National Research Council
Publisher: National Academies Press
ISBN: 0309287812
Category : Mathematics
Languages : en
Pages : 191
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Book Description
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.
Author: Martin Kleppmann
Publisher: "O'Reilly Media, Inc."
ISBN: 1491903104
Category : Computers
Languages : en
Pages : 658
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Book Description
Data is at the center of many challenges in system design today. Difficult issues need to be figured out, such as scalability, consistency, reliability, efficiency, and maintainability. In addition, we have an overwhelming variety of tools, including relational databases, NoSQL datastores, stream or batch processors, and message brokers. What are the right choices for your application? How do you make sense of all these buzzwords? In this practical and comprehensive guide, author Martin Kleppmann helps you navigate this diverse landscape by examining the pros and cons of various technologies for processing and storing data. Software keeps changing, but the fundamental principles remain the same. With this book, software engineers and architects will learn how to apply those ideas in practice, and how to make full use of data in modern applications. Peer under the hood of the systems you already use, and learn how to use and operate them more effectively Make informed decisions by identifying the strengths and weaknesses of different tools Navigate the trade-offs around consistency, scalability, fault tolerance, and complexity Understand the distributed systems research upon which modern databases are built Peek behind the scenes of major online services, and learn from their architectures
Author: Jean-Marc Pierson
Publisher: Springer Science & Business Media
ISBN: 3540312129
Category : Computers
Languages : en
Pages : 151
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Book Description
"The LNCS series reports state-of-the-art results in computer science research, development, and education, at a high level and in both printed and electronic form. Enjoying tight cooperation with the R & D community, with numerous individuals, as well as with prestigious organizations and societies, LNCS has grown into the most comprehensive computer science research forum available." "More recently, several color-cover sublines have been added featuring, beyond a collection of papers, various added-value components; these sublines include: tutorials (textbook-like monographs or collections of lectures given at advanced courses); state-of-the-art surveys (offering complete and mediated coverage of a topic); and hot topics (introducing emergent topics to the broader community)." "In parallel to the printed book, each new volume is published electronically in LNCS Online."--BOOK JACKET.
Author:
Publisher: Microsoft Press
ISBN: 9780735618510
Category : Application software
Languages : en
Pages : 0
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Book Description
Integrate proven performance and scalability techniques throughout the .NET application life cycle--and gain an edge in building better-performing products. This guide presents a robust framework organized by task and role, helping developers, architects, testers, and administrators prioritize and implement the best options at the appropriate time. It offers focused, end-to-end guidance--including processes for modeling performance and techniques for measuring, testing, and fine-tuning your applications. You'll also get tips direct from Microsoft development teams for improving the performance and scalability of managed code; Microsoft ASP.NET, ADO.NET, and SQL Server; Web services; .NET Remoting; XML; and more. The book features a "How To" section that details the steps for a number of specific performance-related tasks, such as adding performance counters and using the common language runtime (CLR) profiler. PATTERNS & PRACTICES guides are reviewed and approved by Microsoft engineering teams, consultants, partners, and customers--delivering accurate, real-world information that's been technically validated and tested.
Author: Daphne Koller
Publisher: MIT Press
ISBN: 0262258358
Category : Computers
Languages : en
Pages : 1270
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Book Description
A general framework for constructing and using probabilistic models of complex systems that would enable a computer to use available information for making decisions. Most tasks require a person or an automated system to reason—to reach conclusions based on available information. The framework of probabilistic graphical models, presented in this book, provides a general approach for this task. The approach is model-based, allowing interpretable models to be constructed and then manipulated by reasoning algorithms. These models can also be learned automatically from data, allowing the approach to be used in cases where manually constructing a model is difficult or even impossible. Because uncertainty is an inescapable aspect of most real-world applications, the book focuses on probabilistic models, which make the uncertainty explicit and provide models that are more faithful to reality. Probabilistic Graphical Models discusses a variety of models, spanning Bayesian networks, undirected Markov networks, discrete and continuous models, and extensions to deal with dynamical systems and relational data. For each class of models, the text describes the three fundamental cornerstones: representation, inference, and learning, presenting both basic concepts and advanced techniques. Finally, the book considers the use of the proposed framework for causal reasoning and decision making under uncertainty. The main text in each chapter provides the detailed technical development of the key ideas. Most chapters also include boxes with additional material: skill boxes, which describe techniques; case study boxes, which discuss empirical cases related to the approach described in the text, including applications in computer vision, robotics, natural language understanding, and computational biology; and concept boxes, which present significant concepts drawn from the material in the chapter. Instructors (and readers) can group chapters in various combinations, from core topics to more technically advanced material, to suit their particular needs.
Author: Gerhard Weikum
Publisher: Morgan Kaufmann
ISBN: 1558605088
Category : Computers
Languages : en
Pages : 881
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Book Description
This book describes the theory, algorithms, and practical implementation techniques behind transaction processing in information technology systems.
Author: Jean-Francois Boulicaut
Publisher: Springer
ISBN: 3540301151
Category : Computers
Languages : en
Pages : 597
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Book Description
The proceedings of ECML/PKDD 2004 are published in two separate, albeit - tertwined,volumes:theProceedingsofthe 15thEuropeanConferenceonMac- ne Learning (LNAI 3201) and the Proceedings of the 8th European Conferences on Principles and Practice of Knowledge Discovery in Databases (LNAI 3202). The two conferences were co-located in Pisa, Tuscany, Italy during September 20–24, 2004. It was the fourth time in a row that ECML and PKDD were co-located. - ter the successful co-locations in Freiburg (2001), Helsinki (2002), and Cavtat- Dubrovnik (2003), it became clear that researchersstrongly supported the or- nization of a major scienti?c event about machine learning and data mining in Europe. We are happy to provide some statistics about the conferences. 581 di?erent papers were submitted to ECML/PKDD (about a 75% increase over 2003); 280 weresubmittedtoECML2004only,194weresubmittedtoPKDD2004only,and 107weresubmitted to both.Aroundhalfofthe authorsforsubmitted papersare from outside Europe, which is a clear indicator of the increasing attractiveness of ECML/PKDD. The Program Committee members were deeply involved in what turned out to be a highly competitive selection process. We assigned each paper to 3 - viewers, deciding on the appropriate PC for papers submitted to both ECML and PKDD. As a result, ECML PC members reviewed 312 papers and PKDD PC members reviewed 269 papers. We accepted for publication regular papers (45 for ECML 2004 and 39 for PKDD 2004) and short papers that were as- ciated with poster presentations (6 for ECML 2004 and 9 for PKDD 2004). The globalacceptance ratewas14.5%for regular papers(17% if we include the short papers).
Author:
Publisher:
ISBN:
Category : Automatic control
Languages : en
Pages :
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Book Description
Author:
Publisher:
ISBN:
Category : Computer industry
Languages : en
Pages : 1878
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Book Description
