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Author: Angela Bonifati
Publisher: Springer Nature
ISBN: 3031018648
Category : Computers
Languages : en
Pages : 166
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Book Description
Graph data modeling and querying arises in many practical application domains such as social and biological networks where the primary focus is on concepts and their relationships and the rich patterns in these complex webs of interconnectivity. In this book, we present a concise unified view on the basic challenges which arise over the complete life cycle of formulating and processing queries on graph databases. To that purpose, we present all major concepts relevant to this life cycle, formulated in terms of a common and unifying ground: the property graph data model—the pre-dominant data model adopted by modern graph database systems. We aim especially to give a coherent and in-depth perspective on current graph querying and an outlook for future developments. Our presentation is self-contained, covering the relevant topics from: graph data models, graph query languages and graph query specification, graph constraints, and graph query processing. We conclude by indicating major open research challenges towards the next generation of graph data management systems.
Author: Angela Bonifati
Publisher: Springer Nature
ISBN: 3031018648
Category : Computers
Languages : en
Pages : 166
Get Book Here
Book Description
Graph data modeling and querying arises in many practical application domains such as social and biological networks where the primary focus is on concepts and their relationships and the rich patterns in these complex webs of interconnectivity. In this book, we present a concise unified view on the basic challenges which arise over the complete life cycle of formulating and processing queries on graph databases. To that purpose, we present all major concepts relevant to this life cycle, formulated in terms of a common and unifying ground: the property graph data model—the pre-dominant data model adopted by modern graph database systems. We aim especially to give a coherent and in-depth perspective on current graph querying and an outlook for future developments. Our presentation is self-contained, covering the relevant topics from: graph data models, graph query languages and graph query specification, graph constraints, and graph query processing. We conclude by indicating major open research challenges towards the next generation of graph data management systems.
Author: Jeff Z. Pan
Publisher: Springer
ISBN: 3319494937
Category : Computers
Languages : en
Pages : 271
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Book Description
This volume contains some lecture notes of the 12th Reasoning Web Summer School (RW 2016), held in Aberdeen, UK, in September 2016. In 2016, the theme of the school was “Logical Foundation of Knowledge Graph Construction and Query Answering”. The notion of knowledge graph has become popular since Google started to use it to improve its search engine in 2012. Inspired by the success of Google, knowledge graphs are gaining momentum in the World Wide Web arena. Recent years have witnessed increasing industrial take-ups by other Internet giants, including Facebook's Open Graph and Microsoft's Satori. The aim of the lecture note is to provide a logical foundation for constructing and querying knowledge graphs. Our journey starts from the introduction of Knowledge Graph as well as its history, and the construction of knowledge graphs by considering both explicit and implicit author intentions. The book will then cover various topics, including how to revise and reuse ontologies (schema of knowledge graphs) in a safe way, how to combine navigational queries with basic pattern matching queries for knowledge graph, how to setup a environment to do experiments on knowledge graphs, how to deal with inconsistencies and fuzziness in ontologies and knowledge graphs, and how to combine machine learning and machine reasoning for knowledge graphs.
Author: Keith McNulty
Publisher: CRC Press
ISBN: 100059727X
Category : Business & Economics
Languages : en
Pages : 266
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Book Description
Handbook of Graphs and Networks in People Analytics: With Examples in R and Python covers the theory and practical implementation of graph methods in R and Python for the analysis of people and organizational networks. Starting with an overview of the origins of graph theory and its current applications in the social sciences, the book proceeds to give in-depth technical instruction on how to construct and store graphs from data, how to visualize those graphs compellingly and how to convert common data structures into graph-friendly form. The book explores critical elements of network analysis in detail, including the measurement of distance and centrality, the detection of communities and cliques, and the analysis of assortativity and similarity. An extension chapter offers an introduction to graph database technologies. Real data sets from various research contexts are used for both instruction and for end of chapter practice exercises and a final chapter contains data sets and exercises ideal for larger personal or group projects of varying difficulty level. Key features: Immediately implementable code, with extensive and varied illustrations of graph variants and layouts. Examples and exercises across a variety of real-life contexts including business, politics, education, social media and crime investigation. Dedicated chapter on graph visualization methods. Practical walkthroughs of common methodological uses: finding influential actors in groups, discovering hidden community structures, facilitating diverse interaction in organizations, detecting political alignment, determining what influences connection and attachment. Various downloadable data sets for use both in class and individual learning projects. Final chapter dedicated to individual or group project examples.
Author: Sourav S. Bhowmick
Publisher: Springer Nature
ISBN: 3031161629
Category : Computers
Languages : en
Pages : 181
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Book Description
This book details recent developments in the emerging area of plug-and-play (PnP) visual subgraph query interfaces (VQI). These PnP interfaces are grounded in the principles of human-computer interaction (HCI) and cognitive psychology to address long-standing limitations to bottom-up search capabilities in graph databases using traditional graph query languages, which often require domain experts and specialist programmers. This book explains how PnP interfaces go against the traditional mantra of VQI construction by taking a data-driven approach and giving end users the freedom to easily and quickly construct and maintain a VQI for any data sources without resorting to coding. The book walks readers through the intuitive PnP interface that uses templates where the underlying graph repository represents the socket and user-specified requirements represent the plug. Hence, a PnP interface enables an end user to change the socket (i.e., graph repository) or the plug (i.e., requirements) as necessary to automatically and effortlessly generate VQIs. The book argues that such a data-driven paradigm creates several benefits, including superior support for visual subgraph query construction, significant reduction in the manual cost of constructing and maintaining a VQI for any graph data source, and portability of the interface across diverse sources and querying applications. This book provides a comprehensive introduction to the notion of PnP interfaces, compares it to its classical manual counterpart, and reviews techniques for automatic construction and maintenance of these new interfaces. In synthesizing current research on plug-and-play visual subgraph query interface management, this book gives readers a snapshot of the state of the art in this topic as well as future research directions.
Author: Sourav S. Bhowmick
Publisher: Springer Nature
ISBN: 3031018613
Category : Computers
Languages : en
Pages : 186
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Book Description
Interacting with graphs using queries has emerged as an important research problem for real-world applications that center on large graph data. Given the syntactic complexity of graph query languages (e.g., SPARQL, Cypher), visual graph query interfaces make it easy for non-programmers to query such graph data repositories. In this book, we present recent developments in the emerging area of visual graph querying paradigm that bridges traditional graph querying with human computer interaction (HCI). Specifically, we focus on techniques that emphasize deep integration between the visual graph query interface and the underlying graph query engine. We discuss various strategies and guidance for constructing graph queries visually, interleaving processing of graph queries and visual actions, visual exploration of graph query results, and automated performance study of visual graph querying frameworks. In addition, this book highlights open problems and new research directions. In summary, in this book, we review and summarize the research thus far into the integration of HCI and graph querying to facilitate user-friendly interaction with graph-structured data, giving researchers a snapshot of the current state of the art in this topic, and future research directions.
Author: Ian Robinson
Publisher: "O'Reilly Media, Inc."
ISBN: 1449356249
Category : Computers
Languages : en
Pages : 224
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Book Description
Discover how graph databases can help you manage and query highly connected data. With this practical book, you’ll learn how to design and implement a graph database that brings the power of graphs to bear on a broad range of problem domains. Whether you want to speed up your response to user queries or build a database that can adapt as your business evolves, this book shows you how to apply the schema-free graph model to real-world problems. Learn how different organizations are using graph databases to outperform their competitors. With this book’s data modeling, query, and code examples, you’ll quickly be able to implement your own solution. Model data with the Cypher query language and property graph model Learn best practices and common pitfalls when modeling with graphs Plan and implement a graph database solution in test-driven fashion Explore real-world examples to learn how and why organizations use a graph database Understand common patterns and components of graph database architecture Use analytical techniques and algorithms to mine graph database information
Author: Aidan Hogan
Publisher: Springer Nature
ISBN: 3031019180
Category : Computers
Languages : en
Pages : 247
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Book Description
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.
Author: Ion Măndoiu
Publisher: Springer Science & Business Media
ISBN: 3642015506
Category : Computers
Languages : en
Pages : 350
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Book Description
This book constitutes the refereed proceedings of the 5th International Symposium on Bioinformatics Research and Applications, ISBRA 2009, held in Fort Lauderdale, FL, USA, in May 2009. The 26 revised full papers presented together four invited papers were carefully reviewed and selected from a total of 55 submissions. The papers cover a wide range of topics, including clustering and classification, gene expression analysis, gene networks, genome analysis, motif finding, pathways, protein structure prediction, protein domain interactions, phylogenetics, and software tools.
Author: Ioannis Pitas
Publisher: CRC Press
ISBN: 1498719058
Category : Computers
Languages : en
Pages : 436
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Book Description
Focused on the mathematical foundations of social media analysis, Graph-Based Social Media Analysis provides a comprehensive introduction to the use of graph analysis in the study of social and digital media. It addresses an important scientific and technological challenge, namely the confluence of graph analysis and network theory with linear alge
Author: Ian Robinson
Publisher: "O'Reilly Media, Inc."
ISBN: 1449356222
Category : Computers
Languages : en
Pages : 161
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Book Description
Discover how graph databases can help you manage and query highly connected data. With this practical book, you’ll learn how to design and implement a graph database that brings the power of graphs to bear on a broad range of problem domains. Whether you want to speed up your response to user queries or build a database that can adapt as your business evolves, this book shows you how to apply the schema-free graph model to real-world problems. Learn how different organizations are using graph databases to outperform their competitors. With this book’s data modeling, query, and code examples, you’ll quickly be able to implement your own solution. Model data with the Cypher query language and property graph model Learn best practices and common pitfalls when modeling with graphs Plan and implement a graph database solution in test-driven fashion Explore real-world examples to learn how and why organizations use a graph database Understand common patterns and components of graph database architecture Use analytical techniques and algorithms to mine graph database information
