Representation of a Sentence using a Polar Fuzzy Neutrosophic Semantic Net

TL;DR

This paper introduces a novel Polar Fuzzy Neutrosophic Semantic Net that extends traditional semantic nets with neutrosophy to represent sentence polarity, enabling emotional understanding in machines.

Contribution

It develops a new semantic net model using neutrosophy to represent sentence polarity and demonstrates its implementation in MATLAB for emotional machine applications.

Findings

Successfully implemented in MATLAB

Can represent positive, neutral, and negative semantics

Facilitates emotion modeling in machines

Abstract

A semantic net can be used to represent a sentence. A sentence in a language contains semantics which are polar in nature, that is, semantics which are positive, neutral and negative. Neutrosophy is a relatively new field of science which can be used to mathematically represent triads of concepts. These triads include truth, indeterminacy and falsehood, and so also positivity, neutrality and negativity. Thus a conventional semantic net has been extended in this paper using neutrosophy into a Polar Fuzzy Neutrosophic Semantic Net. A Polar Fuzzy Neutrosophic Semantic Net has been implemented in MATLAB and has been used to illustrate a polar sentence in English language. The paper demonstrates a method for the representation of polarity in a computers memory. Thus, polar concepts can be applied to imbibe a machine such as a robot, with emotions, making machine emotion representation possible.