Conceptual modeling of cardinality constraints in social publishing

Recent years have witnessed a rise of social publishing, which is a new type of social networking service. Social publishing has certain new features that call for a new way of managing and providing a large volume of documents. A fine data model is expected to evolve dynamically with the up‐to‐date knowledge, especially the associations that emerge in the context of social publishing. This paper first presents a conceptual schema of social publishing, which evolves to combine the association knowledge that reflects hidden associations in the data. A major constraint of concern is cardinality constraint. During the process of enriching a schema, the constraints to be specified should conform to the existing ones. A set of inference rules is presented for modeling with cardinality constraints. The rules are proven to be sound and complete, which helps to derive cardinality constraints from existing ones. The derived cardinality constraints are also proven to be consistent. © 2012 Wiley Periodicals, Inc.

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