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Rehashing the merely obvious:
If a schema declares a vocabulary, the set of all schemas
used by an enterprise is the set of the enterprise vocabulary.
Each instance of a vocabulary is a vector against that
vocabulary, and each vocabulary is a vector against the
enterprise set. The enterprise set is a vector against
its ecosystem of actively communicating entities. Messages
are the terms of enterprise vectors.
If the value of indexing is expressed as the function of the
density of objects in addressable space so that performance
is inversely proportional to the space density (actually, the
address space itself), XML vocabularies increase the
density of the space as well as introducing ambiguity
and uncertainty through semantic loading and can actually
hurt the performance of the system. (yes|no ?)
That's why Bosworth's presentation has merit. The problem
however, is that it simply moves the calculation of the similarity
metric away from the apriori schema declaration into raw
microparsed vector results. A schema is the declaration of a
space where occurrence indicators are a determinant of frequency
and therefore, similarity given a rule that frequent terms are
less important than rare terms within a document (term vectors),
and more important across documents (document vectors).
len
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