Querying Temporal Property Graphs

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Abstract

Nowadays, in many real-world problems, objects are characterized by properties and interactions that evolve over time. Several temporal property graph models associated with query languages are proposed in the literature to manage the temporal and interconnectivity features of such problems. However, they are not widely used due to the lack of a conceptual view. To overcome this drawback, we propose user-oriented operators to analyze temporal evolution of property graphs. We also define translation rules between our operators and existing property graph query languages to implement them directly. To illustrate the feasibility of our solution, we present two case studies based on a Neo4j and an OrientDB implementations of our operators and show some real-world querying examples.

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APA

Andriamampianina, L., Ravat, F., Song, J., & Vallès-Parlangeau, N. (2022). Querying Temporal Property Graphs. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 13295 LNCS, pp. 355–370). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-07472-1_21

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