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Structuring and Merging Distributed Content
Luca Stefanutti, Dietrich Albert, Cord Hockemeyer
113 - 118
Frontiers in Artificial Intelligence and Applications
Volume 127: Towards the Learning Grid
Abstract

A flexible approach for structuring and merging distributed learning object is presented. At the basis of this approach there is a formal representation of a learning object, called attribute structure. Attribute structures are labeled directed graphs representing structured information on the learning objects. When two or more learning objects are merged, the corresponding attribute structures are unified, and the unified structure is attached to the resulting learning object.

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