Sub-Symbolic Knowledge Representation for Evocative Chat-bots

Abstract

The proposed work illustrates how “primitive concepts” can be automatically induced from a text corpus. The pri- mitive concepts are identified by the orthonormal axis of a “conceptual” space induced by a methodology inspired to the Latent Semantic Analysis approach. The methodology represents a natural language sentence by means of a set of rotations of an orthonormal basis in the “conceptual” space. The rotations, triggered by the sequence of words composing the sentence and realized by means of Geomet- ric Algebra rotors, allow to highlight “conceptual” rela- tions that can arise among the primitive concepts.