Multimodal Entity Indexing: A Conceptual Framework for Autonomous Visual Entities in Generative Engine Optimization

Conceptual paper proposing Multimodal Entity Indexing (AVE, IPR, TACS) for Generative Engine Optimization. Draft; not peer reviewed; no empirical data. An experimental protocol for validation is published separately.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-10-29
DOI
https://doi.org/10.5281/zenodo.23757634
Primary Topic
Information Retrieval and Search Behavior
Type
preprint
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preprint

Multimodal Entity Indexing: A Conceptual Framework for Autonomous Visual Entities in Generative Engine Optimization

S. S. Tumengkol
3 links
Zenodo (CERN European Organization for Nuclear Research)
Information Retrieval and Search Behavior
preprint

Multimodal Entity Indexing: A Conceptual Framework for Autonomous Visual Entities in Generative Engine Optimization

S. S. Tumengkol
preprint en

Abstract

Conceptual paper proposing Multimodal Entity Indexing (AVE, IPR, TACS) for Generative Engine Optimization. Draft; not peer reviewed; no empirical data. An experimental protocol for validation is published separately.

Zenodo (CERN European Organization for Nuclear Research)
Information Retrieval and Search Behavior
DOIOpen Access PDFOpenAlex
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Multimodal Entity Indexing: A Conceptual Framework for Autonomous Visual Entities in Generative Engine Optimization — S. S. Tumengkol · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS