Titlebook: Querying Graphs; Angela Bonifati,George Fletcher,Nikolay Yakovets Book 2018 Springer Nature Switzerland AG 2018

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Query Specification,loration. This problem amounts to learning queries from examples and reverse-engineering queries starting from examples that users want or do not want. The complexity of these problems has been studied in-depth and practical implementations have appeared already to witness an increasing interest of

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Data Structures and Indexes,operty graphs should be: (1) concise, i.e., represent a given graph with a small memory footprint; and (2) access-efficient, i.e., allow queries reading and writing as little data as possible to process a given query as quickly as possible on the given hardware architecture. Due to complexity of the

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Query Processing,le, in social networks, one might be interested in looking for simple patterns in relationships between people such as finding persons with shared interests or discovering common friends. On the other hand, in the Web, one can run a completely different graph algorithm such as Page Rank to identify

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Data Models,he property graph model, following the LDBC’s Graph Query Language Task Force [Angles et al., 2018a].. Second, we discuss a number of variations of the property graph model in terms of specializations and structural extensions. This illustrates how the property graph model fits into the family of existing graph models.

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Query Languages,utions are important not only for the study of capabilities and limitations of practical graph query languages but also for the study of graph query processing methods and engineering of practical graph database engines.

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Angela Bonifati,George Fletcher,Hannes Voigt,Nikolay Yakovetss before and after skew impacts and skew collisions as a set of different kinematic elements for each type of impact and collision are discussed and kinematic plans of impacts and corresponding outgoing translator and angular velocities are graphically presented by a series of figures. In conclusion