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Information Modeling And Relational Databases, Halpin,Terry


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Автор: Halpin,Terry
Название:  Information Modeling And Relational Databases
ISBN: 9780443237904
Издательство: Elsevier Science
Классификация:




ISBN-10: 0443237905
Обложка/Формат: Hardback
Страницы: 1032
Вес: 0.45 кг.
Дата издания: 01.07.2024
Издание: 3 ed
Размер: 245 x 198 x 59
Основная тема: Computing
Ссылка на Издательство: Link
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Поставляется из: Европейский союз

How to Prove It : A Structured Approach

Автор: Daniel J. Velleman
Название: How to Prove It : A Structured Approach
ISBN: 1108439535 ISBN-13(EAN): 9781108439534
Издательство: Cambridge Academ
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Цена: 39070.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Proofs play a central role in advanced mathematics and theoretical computer science, and this bestselling text`s third edition will help students transition from solving problems to proving theorems by teaching them the techniques needed to read and write proofs, with a new chapter on number theory and over 150 new exercises.

Designing and Building Enterprise Knowledge Graphs

Автор: Sequeda Juan, Lassila Ora
Название: Designing and Building Enterprise Knowledge Graphs
ISBN: 1636391745 ISBN-13(EAN): 9781636391748
Издательство: Mare Nostrum (Eurospan)
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Цена: 85010.00 T
Наличие на складе: Нет в наличии.
Описание:

This book is a guide to designing and building knowledge graphs from enterprise relational databases in practice. It presents a principled framework centered on mapping patterns to connect relational databases with knowledge graphs, the roles within an organization responsible for the knowledge graph, and the process that combines data and people. The content of this book is applicable to knowledge graphs being built either with property graph or RDF graph technologies.

Knowledge graphs are fulfilling the vision of creating intelligent systems that integrate knowledge and data at large scale. Tech giants have adopted knowledge graphs for the foundation of next-generation enterprise data and metadata management, search, recommendation, analytics, intelligent agents, and more. We are now observing an increasing number of enterprises that seek to adopt knowledge graphs to develop a competitive edge.

In order for enterprises to design and build knowledge graphs, they need to understand the critical data stored in relational databases. How can enterprises successfully adopt knowledge graphs to integrate data and knowledge, without boiling the ocean? This book provides the answers.


Web Data APIs for Knowledge Graphs: Easing Access to Semantic Data for Application Developers

Автор: Meroсo-Peсuela Albert, Lisena Pasquale, Martнnez-Ortiz Carlos
Название: Web Data APIs for Knowledge Graphs: Easing Access to Semantic Data for Application Developers
ISBN: 1636392016 ISBN-13(EAN): 9781636392011
Издательство: Mare Nostrum (Eurospan)
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Цена: 53590.00 T
Наличие на складе: Нет в наличии.
Описание:

This book describes a set of methods, architectures, and tools to extend the data pipeline at the disposal of developers when they need to publish and consume data from Knowledge Graphs (graph-structured knowledge bases that describe the entities and relations within a domain in a semantically meaningful way) using SPARQL, Web APIs, and JSON. To do so, it focuses on the paradigmatic cases of two middleware software packages, grlc and SPARQL Transformer, which automatically build and run SPARQL-based REST APIs and allow the specification of JSON schema results, respectively.

The authors highlight the underlying principles behind these technologies—query management, declarative languages, new levels of indirection, abstraction layers, and separation of concerns—, explain their practical usage, and describe their penetration in research projects and industry.

The book, therefore, serves a double purpose: to provide a sound and technical description of tools and methods at the disposal of publishers and developers to quickly deploy and consume Web Data APIs on top of Knowledge Graphs; and to propose an extensible and heterogeneous Knowledge Graph access infrastructure that accommodates a growing ecosystem of querying paradigms.


Web Data APIs for Knowledge Graphs: Easing Access to Semantic Data for Application Developers

Автор: Meroсo-Peсuela Albert, Lisena Pasquale, Martнnez-Ortiz Carlos
Название: Web Data APIs for Knowledge Graphs: Easing Access to Semantic Data for Application Developers
ISBN: 1636392032 ISBN-13(EAN): 9781636392035
Издательство: Mare Nostrum (Eurospan)
Рейтинг:
Цена: 74850.00 T
Наличие на складе: Нет в наличии.
Описание:

This book describes a set of methods, architectures, and tools to extend the data pipeline at the disposal of developers when they need to publish and consume data from Knowledge Graphs (graph-structured knowledge bases that describe the entities and relations within a domain in a semantically meaningful way) using SPARQL, Web APIs, and JSON. To do so, it focuses on the paradigmatic cases of two middleware software packages, grlc and SPARQL Transformer, which automatically build and run SPARQL-based REST APIs and allow the specification of JSON schema results, respectively.

The authors highlight the underlying principles behind these technologies—query management, declarative languages, new levels of indirection, abstraction layers, and separation of concerns—, explain their practical usage, and describe their penetration in research projects and industry.

The book, therefore, serves a double purpose: to provide a sound and technical description of tools and methods at the disposal of publishers and developers to quickly deploy and consume Web Data APIs on top of Knowledge Graphs; and to propose an extensible and heterogeneous Knowledge Graph access infrastructure that accommodates a growing ecosystem of querying paradigms.


Knowledge Graphs

Автор: Hogan Aidan, Blomqvist Eva, Cochez Michael
Название: Knowledge Graphs
ISBN: 1636392350 ISBN-13(EAN): 9781636392356
Издательство: Mare Nostrum (Eurospan)
Рейтинг:
Цена: 89630.00 T
Наличие на складе: Нет в наличии.
Описание:

This book provides a comprehensive and accessible introduction to knowledge graphs, which have recently garnered notable attention from both industry and academia. Knowledge graphs are founded on the principle of applying a graph-based abstraction to data, and are now broadly deployed in scenarios that require integrating and extracting value from multiple, diverse sources of data at large scale.

The book defines knowledge graphs and provides a high-level overview of how they are used. It presents and contrasts popular graph models that are commonly used to represent data as graphs, and the languages by which they can be queried before describing how the resulting data graph can be enhanced with notions of schema, identity, and context. The book discusses how ontologies and rules can be used to encode knowledge as well as how inductive techniques—based on statistics, graph analytics, machine learning, etc.—can be used to encode and extract knowledge. It covers techniques for the creation, enrichment, assessment, and refinement of knowledge graphs and surveys recent open and enterprise knowledge graphs and the industries or applications within which they have been most widely adopted. The book closes by discussing the current limitations and future directions along which knowledge graphs are likely to evolve.

This book is aimed at students, researchers, and practitioners who wish to learn more about knowledge graphs and how they facilitate extracting value from diverse data at large scale. To make the book accessible for newcomers, running examples and graphical notation are used throughout. Formal definitions and extensive references are also provided for those who opt to delve more deeply into specific topics.


Knowledge Graphs

Автор: Hogan Aidan, Blomqvist Eva, Cochez Michael
Название: Knowledge Graphs
ISBN: 1636392377 ISBN-13(EAN): 9781636392370
Издательство: Mare Nostrum (Eurospan)
Рейтинг:
Цена: 111810.00 T
Наличие на складе: Нет в наличии.
Описание:

This book provides a comprehensive and accessible introduction to knowledge graphs, which have recently garnered notable attention from both industry and academia. Knowledge graphs are founded on the principle of applying a graph-based abstraction to data, and are now broadly deployed in scenarios that require integrating and extracting value from multiple, diverse sources of data at large scale.

The book defines knowledge graphs and provides a high-level overview of how they are used. It presents and contrasts popular graph models that are commonly used to represent data as graphs, and the languages by which they can be queried before describing how the resulting data graph can be enhanced with notions of schema, identity, and context. The book discusses how ontologies and rules can be used to encode knowledge as well as how inductive techniques—based on statistics, graph analytics, machine learning, etc.—can be used to encode and extract knowledge. It covers techniques for the creation, enrichment, assessment, and refinement of knowledge graphs and surveys recent open and enterprise knowledge graphs and the industries or applications within which they have been most widely adopted. The book closes by discussing the current limitations and future directions along which knowledge graphs are likely to evolve.

This book is aimed at students, researchers, and practitioners who wish to learn more about knowledge graphs and how they facilitate extracting value from diverse data at large scale. To make the book accessible for newcomers, running examples and graphical notation are used throughout. Formal definitions and extensive references are also provided for those who opt to delve more deeply into specific topics.


Data Management in Machine Learning Systems

Автор: Matthias Boehm, Arun Kumar, Jun Yang
Название: Data Management in Machine Learning Systems
ISBN: 1681734982 ISBN-13(EAN): 9781681734989
Издательство: Mare Nostrum (Eurospan)
Рейтинг:
Цена: 87780.00 T
Наличие на складе: Нет в наличии.
Описание: Large-scale data analytics using machine learning (ML) underpins many modern data-driven applications. ML systems provide means of specifying and executing these ML workloads in an efficient and scalable manner. Data management is at the heart of many ML systems due to data-driven application characteristics, data-centric workload characteristics, and system architectures inspired by classical data management techniques. In this book, we follow this data-centric view of ML systems and aim to provide a comprehensive overview of data management in ML systems for the end-to-end data science or ML lifecycle. We review multiple interconnected lines of work: (1) ML support in database (DB) systems, (2) DB-inspired ML systems, and (3) ML lifecycle systems. Covered topics include: in-database analytics via query generation and user-defined functions, factorized and statistical-relational learning; optimizing compilers for ML workloads; execution strategies and hardware accelerators; data access methods such as compression, partitioning and indexing; resource elasticity and cloud markets; as well as systems for data preparation for ML, model selection, model management, model debugging, and model serving. Given the rapidly evolving field, we strive for a balance between an up-to-date survey of ML systems, an overview of the underlying concepts and techniques, as well as pointers to open research questions. Hence, this book might serve as a starting point for both systems researchers and developers.

Building Smart Cities

Автор: Stimmel
Название: Building Smart Cities
ISBN: 1498702767 ISBN-13(EAN): 9781498702768
Издательство: Taylor&Francis
Рейтинг:
Цена: 117390.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The term "smart city" defines the new urban environment, one that is designed for performance through information and communication technologies. Given that the majority of people across the world will live in urban environments within the next few decades, it's not surprising that massive effort and investment is being placed into efforts to develop strategies and plans for achieving "smart" urban growth. Building Smart Cities: Analytics, ICT, and Design Thinking explains the technology and a methodology known as design thinking for building smart cities. Information and communications technologies form the backbone of smart cities. A comprehensive and robust data analytics program enables the right choices to be made in building these cities. Design thinking helps to create smart cities that are both livable and able to evolve. This book examines all of these components in the context of smart city development and shows how to use them in an integrated manner. Using the principles of design thinking to reframe the problems of the smart city and capture the real needs of people living in a highly efficient urban environment, the book helps city planners and technologists through the following: Presentation of the relevant technologies required for coordinated, efficient cities Exploration of the latent needs of community stakeholders in a culturally appropriate context Discussion of the tested approaches to ideation, design, prototyping, and building or retrofitting smart cities Proposal of a model for a viable smart city project The smart city vision that we can create an optimized society through technology is hypothetical at best and reflects the failed repetition through the ages of equating scientific progress with positive social change. Up until now, despite our best hopes and efforts, technology has yet to bring an end to scarcity or suffering. Technical innovation, instead, can and should be directed in the service of our shared cultural values, especially within the rapidly growing urban milieu. In Building Smart Cities: Analytics, ICT, and Design Thinking, the author discusses the need to focus on creating human-centered approaches to our cities that integrate our human needs and technology to meet our economic, environmental, and existential needs. The book shows how this approach can lead to innovative, livable urban environments that are realizable, practical, and economically and environmentally sustainable.

New Trends in Databases and Information Systems

Автор: Ivanovi?
Название: New Trends in Databases and Information Systems
ISBN: 3319440659 ISBN-13(EAN): 9783319440651
Издательство: Springer
Рейтинг:
Цена: 55900.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book constitutes the thoroughly refereed short papers, workshops and Doctoral Consortium papers of the 20th East European Conference on Advances in Databases and Information Systems, ADBIS 2016, held in Prague, Czech Republic, in August 2016.The 11 short papers and one historical paper were carefully selected and reviewed from 85 submissions. The rest of papers was selected from reviewing processes of 2 workshops and Doctoral Consortium. The papers are organized in topical sections on ADBIS Short Papers, Third International Workshop on Big Data Applications and Principles (BigDap 2016), Second International Workshop on Data Centered Smart Applications (DCSA 2016) and ADBIS Doctoral Consortium.

Data Analytics

Название: Data Analytics
ISBN: 1138035483 ISBN-13(EAN): 9781138035485
Издательство: Taylor&Francis
Рейтинг:
Цена: 74510.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Effective presentation of analytical results is the key to close a project successfully. With the meteoric rise in the popularity of data science and analytics, business executives focus on analytics` strategic interpretation and managerial implications, as well as value creation from analytics.

The 3D Global Spatial Data Model -

Автор: Burkholder
Название: The 3D Global Spatial Data Model -
ISBN: 1498722164 ISBN-13(EAN): 9781498722162
Издательство: Taylor&Francis
Рейтинг:
Цена: 158230.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This new second edition demystifies the concepts of spatial data accuracy and provides mathematical clarity to issues of network accuracy and local accuracy. Ideal for both beginner and advanced levels, this book also provides guidance and insight on how to link to the data collected and stored in legacy systems.

Advances in Probabilistic Databases for Uncertain Information Management

Автор: Zongmin Ma; Li Yan
Название: Advances in Probabilistic Databases for Uncertain Information Management
ISBN: 3642375081 ISBN-13(EAN): 9783642375088
Издательство: Springer
Рейтинг:
Цена: 121890.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:

1 Research in Probabilistic Spatiotemporal Databases:
The SPOT Framework.-

2 A Probabilistic Object-Oriented Database Model with
Fuzzy Measures.-

3 Probabilistic XML: Models and Complexity.-

4 Uncertain Data: Representations, Query Processing,
and Applications.-

5 A Theoretically-Sound Approach for OLAPing Uncertain
and Imprecise Multidimensional Data Streams.-

6 Tractable Probabilistic Description Logic Programs.



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