Deeply Semantic Inductive Spatio-Temporal Learning

Jakob Suchan; Mehul Bhatt; Carl Schultz

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arXiv · 1608.02693

Deeply Semantic Inductive Spatio-Temporal Learning

Jakob Suchan·Mehul Bhatt·Carl Schultz

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Abstract

We present an inductive spatio-temporal learning framework rooted in inductive logic programming. With an emphasis on visuo-spatial language, logic, and cognition, the framework supports learning with relational spatio-temporal features identifiable in a range of domains involving the processing and interpretation of dynamic visuo-spatial imagery. We present a prototypical system, and an example application in the domain of computing for visual arts and computational cognitive science.

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Jakob Suchan, Mehul Bhatt, Carl Schultz. 2016-08-09. Deeply Semantic Inductive Spatio-Temporal Learning. https://arxiv.org/abs/1608.02693

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