The goal of semantic analysis is to decipher the intent or meaning behind a narrative. With the power of machine learning, this often involves analyzing millions of combinations of word stems and grammatical structures. The good news is sometimes a simpler approach is better. KM World brought this interesting information to us in their article, “The hidden world of deep semantics.”
We can streamline the approach by focusing on only a few dozen motor reflex arcs called phonemes. They are the basic elements of speech that our physiology makes available for us to convey an infinite number of possible words. If you combine them with a few dozen semantic primes, it results in a more manageable set of conceptual structures without diluting the results.
This a far less complicated approach to semantic analysis that links narrative to the underlying knowledge, including the emotions behind it. From counterterrorism to consumer marketing, the potential is astounding.
Melody K. Smith
Sponsored by Access Innovations, the world leader in thesaurus, ontology, and taxonomy creation and metadata application.