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Human Interaction with Graphs [electronic resource] / by Sourav S. Bhowmick, Byron Choi, Chengkai Li.

By: Bhowmick, Sourav S [author.].
Contributor(s): Choi, Byron [author.] | Li, Chengkai [author.] | SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Synthesis Lectures on Data Management: Publisher: Cham : Springer International Publishing : Imprint: Springer, 2018Edition: 1st ed. 2018.Description: XXII, 186 p. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783031018619.Subject(s): Computer networks  | Data structures (Computer science) | Information theory | Computer Communication Networks | Data Structures and Information TheoryAdditional physical formats: Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleDDC classification: 004.6 Online resources: Click here to access online
Contents:
Foreword -- Preface -- Acknowledgments -- Introduction -- Background -- Guidance for Visual Query Formulation -- Blending Human Interactions and Graph Query Processing -- Blending Interactions and Query Processing on Large Networks -- Human Interaction with Query Results -- Simulation of Visual Subgraph Query Formulation -- The Road Ahead -- Bibliography -- Authors' Biographies.
In: Springer Nature eBookSummary: 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.
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Foreword -- Preface -- Acknowledgments -- Introduction -- Background -- Guidance for Visual Query Formulation -- Blending Human Interactions and Graph Query Processing -- Blending Interactions and Query Processing on Large Networks -- Human Interaction with Query Results -- Simulation of Visual Subgraph Query Formulation -- The Road Ahead -- Bibliography -- Authors' Biographies.

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.

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