
We investigate the problem of constructing a shape graph that describes the structure of a given graph database. We employ the framework of grammatical inference, where the objective is to find an inference algorithm that is both sound, i.e., always producing a schema that validates the input graph, and complete, i.e., able to produce any schema, within a given class of schemas, provided that a sufficiently informative input graph is presented. We identify a number of fundamental limitations that preclude feasible inference. We present inference algorithms based on natural approaches that allow to infer schemas that we argue to be of practical importance.
Inference, Schema, Learning, [INFO.INFO-DB] Computer Science [cs]/Databases [cs.DB], Containment, Fitting, Minimality, 004, RDF, ddc: ddc:004
Inference, Schema, Learning, [INFO.INFO-DB] Computer Science [cs]/Databases [cs.DB], Containment, Fitting, Minimality, 004, RDF, ddc: ddc:004
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