Predication-based Semantic Indexing (PSI) is an approach to generat- ing high-dimensional vector representations of concept-relation-concept triplets. In this paper, we develop a variant of PSI that accommodates estimation of the probability of encountering a particular predication (such as uoxetine TREATS major depressive disorder) in a collection of predications concerning a con- cept of interest (such as major depressive disorder). PSI leverages reversible vector transformations provided by representational approaches known as Vector Symbolic Architectures (VSA). To embed probabilities we develop a novel VSA variant, Hermitian Holographic Reduced Representations, with improvements in predictive modeling experiments. The probabilistic interpretation this facilitates reveals previously unrecognized connections between PSI and quantum theory - perhaps most notably that PSI's estimation of relatedness across multiple rea- soning pathways corresponds to the estimation of the probability of traversing indistinguishable pathways in accordance with the rules of quantum probability.
['Trevor Cohen', 'Dominic Widdows']
Embedding Probabilities in Predication Space with Hermitian Holographic Reduced Representations