  Semi-structured and unstructured data management is challenging, but many of
the problems encountered are analogous to problems already addressed in the
relational context. In the area of information extraction, for example, the
shift from engineering ad hoc, application-specific extraction rules towards
using expressive languages such as CPSL and AQL creates opportunities to
propose solutions that can be applied to a wide range of extraction programs.
In this work, we focus on extracted view maintenance, a problem that is
well-motivated and thoroughly addressed in the relational setting. In
particular, we formalize and address the problem of keeping extracted relations
consistent with source documents that can be arbitrarily updated. We formally
characterize three classes of document updates, namely those that are
irrelevant, autonomously computable, and pseudo-irrelevant with respect to a
given extractor. Finally, we propose algorithms to detect pseudo-irrelevant
document updates with respect to extractors that are expressed as document
spanners, a model of information extraction inspired by SystemT.
