Search Engine Optimization for Vector-Based Image Search

Metadata

Publisher: SMPTE — Hollywood, CA
Doc Type: Conference Paper
Content Type: Original Research
Volume: 00, pp. 1–11
Abstract: Vector-based image search, which represents images and search queries as vectors in a high-dimensional space, performs image search by identifying images whose vector representations closely match the vector representation of the query. Search engine optimization has been traditionally achieved by using relevant keywords to increase organic search engine discoverability. For images to be surfaced as a result of a search query, these relevant keywords have been inserted in the page that hosts the image or embedded directly into an image as metadata that can be decoded and indexed by a text-based search engine. However, when a search engine uses vectors to operate, the static nature of an image's vector representation prevents adaptation of content to increase discoverability. In this paper we present a novel approach to alter an image in a way that enhances its discoverability with a known vector-based search engine while limiting the visual impacts of these alterations for an average user. The alteration is guided by the maximization of intended search queries and the minimization of unwanted search queries.
Publication Date: 2024-10-21
DOI: 10.5594/MOO/3046
ISBN: [object Object]
Link: https://doi.org/10.5594/MOO/3046
Author(s): Jean-Yves Couleaud
Mathew Adams
Ning Xu
Keyword(s): Vector Search, Image Search Engine Optimization
Copyright: © 2024 SMPTE

Source Data (JSON)

Full registry record with provenance metadata. Open directly: /api/doc/10.5594-MOO-3046.json

Reference this Doc

Plain text (ISO 690 compliant)

Preview:

Jean-Yves Couleaud, Mathew Adams, and Ning Xu; Search Engine Optimization for Vector-Based Image Search, MTS 2024, Article 35 (pp. 1 to 11); SMPTE, 2024, ISBN: [object Object]. Available at https://doi.org/10.5594/MOO/3046

Snippet:

Jean-Yves Couleaud, Mathew Adams, and Ning Xu; Search Engine Optimization for Vector-Based Image Search, MTS 2024, Article 35 (pp. 1 to 11); SMPTE, 2024, ISBN: [object Object]. Available at https://doi.org/10.5594/MOO/3046

HTML (ISO 690 compliant)

Preview:

Snippet:

<span class="citation">Jean-Yves Couleaud, Mathew Adams, and Ning Xu; <cite>Search Engine Optimization for Vector-Based Image Search</cite>, MTS 2024, Article 35 (pp. 1 to 11); SMPTE, 2024, ISBN: [object Object]. Available at <a href="https://doi.org/10.5594/MOO/3046" target="_blank" rel="noopener">https://doi.org/10.5594/MOO/3046</a></span>

SMPTE's HTML Pub

Preview:

Jean-Yves Couleaud, Mathew Adams, and Ning Xu; Search Engine Optimization for Vector-Based Image Search, MTS 2024, Article 35 (pp. 1 to 11); SMPTE, 2024, ISBN: [object Object]
doi: 10.5594/MOO/3046
url: https://doi.org/10.5594/MOO/3046

Snippet:

<li>
Jean-Yves Couleaud, Mathew Adams, and Ning Xu; <cite id="bib-10-5594-moo-3046">Search Engine Optimization for Vector-Based Image Search</cite>, MTS 2024, Article 35 (pp. 1 to 11); SMPTE, 2024, ISBN: [object Object]
<span class="doi">10.5594/MOO/3046</span>
</li>