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Title Bisimulations on Data Graphs
Authors Sergio Abriola, Pablo Barceló, Diego Figueira, Santiago Figueira
Publication date 2016
Abstract Bisimulation provides structural conditions to
characterize
indistinguishability between nodes on graph-like structures from an external
observer. It is a fundamental notion used in many areas. However, many
applications use graphs where nodes have data, and where observers can test
for equality or inequality of data values (e.g., asking the attribute "name"
of a node to be different from that of all its neighbors). The present work
constitutes a first investigation of "data aware"' bisimulations on data
graphs. We study the problem of computing such bisimulations, based on the
observational indistinguishability for XPath -- a language that extends
modal logic with tests for data equality. We show that in general the
problem is pspace-complete, but identify several restrictions that yield
better complexity bounds (coNP, ptime) by controlling suitable parameters of
the problem; namely, the amount of em non-locality allowed, and the class of
models considered (graph, DAG, tree). In particular, this analysis yields a
hierarchy of tractable fragments.
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Pages 309-318
Conference name International Conference on Principles of Knowledge Representation and Reasoning
Publisher Association for the Advancement of Artificial Intelligence (www.aaai.org)
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