Semantic Signatures℠ approaches meaning of words from the perspective of their context. In the past couple of months, there has been extensive discussion here and elsewhere about how this differs from RDF, the basis for the Semantic Web. The simplest answer is that we are data-driven where RDF is model-driven.

This dichotomy is nothing new. In fact, if we look at semantics over a hundred years ago, we see the empirical idea of contextual semantics in the structural linguistics of  Ferdinand de Saussure in contrast to the logical formulation of meaning in the predicate calculus of Bertrand Russell and Alfred North Whitehead. The former inferred meaning from the comparative analysis of text; the latter defined a mapping between text and a formal model of possible meanings.

The model-driven approach became less popular after the logician Kurt Gödel proved the incompleteness of all non-trivial logical systems in the 1930′s. Structural linguistics then became the favored approach until Noam Chomsky put the study of language back on a formal basis in the 1950′s, and the semantics of language also tilted to the formal in order to be more consistent with the study of syntax.

This is not to say that one approach is right and the other is wrong. The choice of approach to take should really depend on one’s circumstances. If one has available an appropriate logical model, which today might correspond to a taxonomy and a formal way to relate taxonomic entities, then the model-driven option is compelling. On the other hand, if an appropriate model is lacking or incomplete, but there is plenty of tagged text data to work from, then the data-driven option should be considered.

One can always in fact choose to work with the best of both worlds. We are not the sole providers of data-driven semantic technology, but our statistical characterization of meaning is probably de Saussure himself might have done it if he had access to the Worldwide Web and 21st Century cloud computing.