Skyline-based exploration of temporal property graphs
CoRR(2024)
摘要
In this paper, we focus on temporal property graphs, that is, property graphs
whose labeled nodes and edges as well as the values of the properties
associated with them may change with time. For instance, consider a
bibliographic network, with nodes representing authors and conferences with
properties such as gender and location respectively, and edges representing
collaboration between authors and publications in conferences. A key challenge
in studying temporal graphs lies in detecting interesting events in their
evolution, defined as time intervals of significant stability, growth, or
shrinkage. To address this challenge, we build aggregated graphs, where nodes
are grouped based on the values of their properties, and seek events at the
aggregated level, for example, time intervals of significant growth in the
collaborations between authors of the same gender. To locate such events, we
propose a novel approach based on unified evolution skylines. A unified
evolution skyline assesses the significance of an event in conjunction with the
duration of the interval in which the event occurs. Significance is measured by
a set of counts, where each count refers to the number of graph elements that
remain stable, are created, or deleted, for a specific property value. For
example, for property gender, we measure the number of female-female,
female-male, and male-male collaborations. Lastly, we share experimental
findings that highlight the efficiency and effectiveness of our approach.
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