Big Data Integration Theory
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Big Data Integration Theory
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Author : Zoran Majkić
language : en
Publisher: Springer Science & Business Media
Release Date : 2014-01-23
Big Data Integration Theory written by Zoran Majkić and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-01-23 with Computers categories.
This book presents a novel approach to database concepts, describing a categorical logic for database schema mapping based on views, within a framework for database integration/exchange and peer-to-peer. Database mappings, database programming languages, and denotational and operational semantics are discussed in depth. An analysis method is also developed that combines techniques from second order logic, data modeling, co-algebras and functorial categorial semantics. Features: provides an introduction to logics, co-algebras, databases, schema mappings and category theory; describes the core concepts of big data integration theory, with examples; examines the properties of the DB category; defines the categorial RDB machine; presents full operational semantics for database mappings; discusses matching and merging operators for databases, universal algebra considerations and algebraic lattices of the databases; explores the relationship of the database weak monoidal topos w.r.t. intuitionistic logic.
Big Data Integration
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Author : Xin Luna Dong
language : en
Publisher: Morgan & Claypool Publishers
Release Date : 2015-02-01
Big Data Integration written by Xin Luna Dong and has been published by Morgan & Claypool Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-02-01 with Computers categories.
The big data era is upon us: data are being generated, analyzed, and used at an unprecedented scale, and data-driven decision making is sweeping through all aspects of society. Since the value of data explodes when it can be linked and fused with other data, addressing the big data integration (BDI) challenge is critical to realizing the promise of big data. BDI differs from traditional data integration along the dimensions of volume, velocity, variety, and veracity. First, not only can data sources contain a huge volume of data, but also the number of data sources is now in the millions. Second, because of the rate at which newly collected data are made available, many of the data sources are very dynamic, and the number of data sources is also rapidly exploding. Third, data sources are extremely heterogeneous in their structure and content, exhibiting considerable variety even for substantially similar entities. Fourth, the data sources are of widely differing qualities, with significant differences in the coverage, accuracy and timeliness of data provided. This book explores the progress that has been made by the data integration community on the topics of schema alignment, record linkage and data fusion in addressing these novel challenges faced by big data integration. Each of these topics is covered in a systematic way: first starting with a quick tour of the topic in the context of traditional data integration, followed by a detailed, example-driven exposition of recent innovative techniques that have been proposed to address the BDI challenges of volume, velocity, variety, and veracity. Finally, it presents merging topics and opportunities that are specific to BDI, identifying promising directions for the data integration community.
Intensional First Order Logic
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Author : Zoran Majkic
language : en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date : 2022-09-05
Intensional First Order Logic written by Zoran Majkic and has been published by Walter de Gruyter GmbH & Co KG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-09-05 with Computers categories.
This book introduces the properties of conservative extensions of First Order Logic (FOL) to new Intensional First Order Logic (IFOL). This extension allows for intensional semantics to be used for concepts, thus affording new and more intelligent IT systems. Insofar as it is conservative, it preserves software applications and constitutes a fundamental advance relative to the current RDB databases, Big Data with NewSQL, Constraint databases, P2P systems and Semantic Web applications. Moreover, the many-valued version of IFOL can support the AI applications based on many-valued logics.
Big Data And Information Theory
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Author : Jiuping Xu
language : en
Publisher: Routledge
Release Date : 2024-01-29
Big Data And Information Theory written by Jiuping Xu and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-01-29 with Business & Economics categories.
This book brings together leading researchers and engineers to exchange and share their experiences and research results about big data and information theory applications in various areas.
Intensional First Order Logic
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Author : Zoran Majkic
language : en
Publisher: de Gruyter
Release Date : 2022-09-05
Intensional First Order Logic written by Zoran Majkic and has been published by de Gruyter this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-09-05 with categories.
Modular Ontologies
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Author : Heiner Stuckenschmidt
language : en
Publisher: Springer
Release Date : 2009-05-17
Modular Ontologies written by Heiner Stuckenschmidt and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-05-17 with Computers categories.
This book constitutes a collection of research achievements mature enough to provide a firm and reliable basis on modular ontologies. It discusses the recent concepts, theories and techniques for knowledge modularization.
Big Data Concepts Theories And Applications
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Author : Shui Yu
language : en
Publisher: Springer
Release Date : 2016-03-03
Big Data Concepts Theories And Applications written by Shui Yu and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-03-03 with Computers categories.
This book covers three major parts of Big Data: concepts, theories and applications. Written by world-renowned leaders in Big Data, this book explores the problems, possible solutions and directions for Big Data in research and practice. It also focuses on high level concepts such as definitions of Big Data from different angles; surveys in research and applications; and existing tools, mechanisms, and systems in practice. Each chapter is independent from the other chapters, allowing users to read any chapter directly. After examining the practical side of Big Data, this book presents theoretical perspectives. The theoretical research ranges from Big Data representation, modeling and topology to distribution and dimension reducing. Chapters also investigate the many disciplines that involve Big Data, such as statistics, data mining, machine learning, networking, algorithms, security and differential geometry. The last section of this book introduces Big Data applications from different communities, such as business, engineering and science. Big Data Concepts, Theories and Applications is designed as a reference for researchers and advanced level students in computer science, electrical engineering and mathematics. Practitioners who focus on information systems, big data, data mining, business analysis and other related fields will also find this material valuable.
Knowledge Graphs And Big Data Processing
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Author : Valentina Janev
language : en
Publisher: Springer Nature
Release Date : 2020-07-15
Knowledge Graphs And Big Data Processing written by Valentina Janev and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-15 with Computers categories.
This open access book is part of the LAMBDA Project (Learning, Applying, Multiplying Big Data Analytics), funded by the European Union, GA No. 809965. Data Analytics involves applying algorithmic processes to derive insights. Nowadays it is used in many industries to allow organizations and companies to make better decisions as well as to verify or disprove existing theories or models. The term data analytics is often used interchangeably with intelligence, statistics, reasoning, data mining, knowledge discovery, and others. The goal of this book is to introduce some of the definitions, methods, tools, frameworks, and solutions for big data processing, starting from the process of information extraction and knowledge representation, via knowledge processing and analytics to visualization, sense-making, and practical applications. Each chapter in this book addresses some pertinent aspect of the data processing chain, with a specific focus on understanding Enterprise Knowledge Graphs, Semantic Big Data Architectures, and Smart Data Analytics solutions. This book is addressed to graduate students from technical disciplines, to professional audiences following continuous education short courses, and to researchers from diverse areas following self-study courses. Basic skills in computer science, mathematics, and statistics are required.
Managing Big Data Integration In The Public Sector
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Author : Aggarwal, Anil
language : en
Publisher: IGI Global
Release Date : 2015-11-12
Managing Big Data Integration In The Public Sector written by Aggarwal, Anil and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-11-12 with Computers categories.
The era of rapidly progressing technology we live in generates vast amounts of data; however, the challenge exists in understanding how to aggressively monitor and make sense of this data. Without a better understanding of how to collect and manage such large data sets, it becomes increasingly difficult to successfully utilize them. Managing Big Data Integration in the Public Sector is a pivotal reference source for the latest scholarly research on the application of big data analytics in government contexts and identifies various strategies in which big data platforms can generate improvements within that sector. Highlighting issues surrounding data management, current models, and real-world applications, this book is ideally designed for professionals, government agencies, researchers, and non-profit organizations interested in the benefits of big data analytics applied in the public sphere.
Principles Of Data Integration
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Author : AnHai Doan
language : en
Publisher: Elsevier
Release Date : 2012-06-25
Principles Of Data Integration written by AnHai Doan and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-06-25 with Computers categories.
How do you approach answering queries when your data is stored in multiple databases that were designed independently by different people? This is first comprehensive book on data integration and is written by three of the most respected experts in the field. This book provides an extensive introduction to the theory and concepts underlying today's data integration techniques, with detailed, instruction for their application using concrete examples throughout to explain the concepts. Data integration is the problem of answering queries that span multiple data sources (e.g., databases, web pages). Data integration problems surface in multiple contexts, including enterprise information integration, query processing on the Web, coordination between government agencies and collaboration between scientists. In some cases, data integration is the key bottleneck to making progress in a field. The authors provide a working knowledge of data integration concepts and techniques, giving you the tools you need to develop a complete and concise package of algorithms and applications. Offers a range of data integration solutions enabling you to focus on what is most relevant to the problem at hand Enables you to build your own algorithms and implement your own data integration applications