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July 8, 2026Open Access

Dictionary and technical nomenclature of Generative Engine Optimization (GEO)

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Authors

IBIsaías Blanco

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Overview

Standardized ontology of machine learning and minimalist design unifies Generative Engine Optimization concepts.

Key Points

  • This document aims to establish a standardized ontology and technical dictionary for Generative Engine Optimization.
  • Developed an ontology that unifies machine learning and design principles under the Kūkan-Ha framework.
  • Addressed issues of semantic and structural ambiguity in GEO-related vectors.
  • Created a technical dictionary to provide a common language for the evolving digital ecosystem.
  • Identified key challenges in Generative Engine Optimization due to algorithmic invisibility.
  • Proposed a framework to improve the organization of knowledge in machine-readable formats.
  • Highlighted the need for rigorous standards amid the rising complexity of web positioning.

Cite This Study

Isaías Blanco (2026) studied this question.

synapsesocial.com/papers/6a4dea28d2ea289ef6283f87https://doi.org/10.5281/zenodo.21225769
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