Parameter-free Model of Rank Polysemantic Distribution

TL;DR

This paper introduces a minimal-parameter model for rank polysemantic distribution that aims to describe the distribution's dependence using few or no fitting parameters, potentially simplifying analysis.

Contribution

It proposes a novel, parameter-free model for rank polysemantic distribution based on immediate features, reducing the need for extensive fitting.

Findings

Model achieves minimal parameter fitting

Potential for direct dependence description

Simplifies analysis of polysemantic distributions

Abstract

A model of rank polysemantic distribution with a minimal number of fitting parameters is offered. In an ideal case a parameter-free description of the dependence on the basis of one or several immediate features of the distribution is possible.