Representation of a Sentence using a Polar Fuzzy Neutrosophic Semantic Net

Abstract

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 computer's memory. Thus, polar concepts can be applied to imbibe a machine such as a robot, with emotions, making machine emotion representation possible.

How Objective a Neutral Word Is? A Neutrosophic Approach for the Objectivity Degrees of Neutral Words

“…Let X be a universe of discourse, with a generic element in X denoted by x, then a neutrosophic set [32] A is an object having the form A = {< x : t A (x), i A (x), f A (x) >, x ∈ X} where the functions t, i, f : X → [0, 1] define respectively the degree of membership (or truth), the degree of indeterminacy and the degree of non-membership (or falsehood) of the element x ∈ X to the set A fulfilling the condition 0 ≤ t A + i A + f A ≤ 3. As stated in [1], the three notions of truth, indeterminacy and falsehood can be substituted by the notions of positivity, neutrality and negativity, respectively.…”

“…This polarity is usually considered as having three possible values: positive, negative or neutral. Representation of the polarity in a natural language utterance, more precisely of its positivity, neutrality and negativity scores, has been a long-standing problem in NLP [1], the solving of which was attempted by various knowledge representation techniques including frames [2], conceptual dependency or semantic nets [3]. An extension of semantic nets was proposed under the name of fuzzy semantic nets [4][5][6] in order to include inexactitude and imprecision.…”