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Introducing The Word-Sensibility Model

A Theoretical Look at the Role of Words for Artificial Intelligence: Commonsense Knowledge Representation and Reference Frames 

Site Summary: There are countless situations that humans can recognize and machines can not. To enhance machine awareness of commonsense concepts, the idea is to analyze the words of a text utilizing reference frames. We call it word-sensibility. The goal is textual analysis to assess word sense by simulating human responsiveness. That is, the ability to act quickly and positively to situations in the world. In this way, machines can make better sense of the things that people typically know. A conceptual model and propositions are proposed that could form the basis for further research.

The Quadranym Model of Word-Sensibility (Q): An Ecological Systems Perspective On Word-Level Concepts & Contextual Unitizations — Non-Mental-Representation Representation — Action Based Theory of Context.

Q: A method to analyze and cluster words – an ontological alignment system to represent dynamic word relations in units, scripts and layers.

“To understand is to experience harmony between what we aim at and what is given, between the intention and the performance – and the body is our anchorage in the world. ”  ―  Maurice Merleau-Ponty




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