Title: A Mathematical Framework for Contextual Data Modulation via Conflict Analysis

Abstract: This paper introduces a generalized operator-based mathematical framework designed to explicitly capture the structural divergences between raw and contextual data. By treating conflict as a local, directional, and context-dependent metric, the proposed structure unifies elements such as weighting mechanisms, scale behavior, and output mapping under a single abstract operator. Unlike existing methods that view conflict merely as an implicit byproduct of the optimization process, this approach defines conflict as an independent, component-level mathematical entity rooted in operator theory. Consequently, the framework remains distinct from any specific learning algorithm or optimization technique, offering a versatile structural foundation adaptable to a wide variety of problem classes.

Source: arXiv Generated at: 2026-06-02 00:00:00 UTC