Search Engine Optimization for Vector-Based Image Search

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.

Published

2024-10-21

Content type

Original Research

Keywords

vector search, image search engine optimization

DOI

10.5594/MOO/3046

ISBN

978-1-61482-965-2