Abstract
Recently, people, devices, processes, and other entities have been more connected than at any other point in history. In general, a graph is a natural, neat, and flexible structure to model the complex relationships, interactions, and interdependencies between objects (Fig. 4.1). In particular, each graph consists of nodes (or vertices) that represent objects and edges (or links) that represent the relationships among the graph nodes. Graphs have been widely used to represent datasets in a wide range of application domains such as social science, astronomy, computational biology, telecommunications, computer networks, semantic Web, protein networks, and many others (Sakr and Pardede, Graph Data Management: Techniques and Applications, 2011 [73]).
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Sakr, S. (2016). Large-Scale Graph Processing Systems. In: Big Data 2.0 Processing Systems. SpringerBriefs in Computer Science. Springer, Cham. https://doi.org/10.1007/978-3-319-38776-5_4
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DOI: https://doi.org/10.1007/978-3-319-38776-5_4
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