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Tag, You’re It: How to Better Predict How Users Will Label Images for Search Queries

By Lori Cameron

By Lori Cameron on
July 28, 2017

blue hashtags on pile of white hashtagsblue hashtags on pile of white hashtags

For a long time, the conventional wisdom about tagging images was to use clear, precise words that interpret the picture exactly. For example, with the ubiquitous cat photo, you would use (cat, cats, kitten, cat lover, tabby). Pretty straightforward.

However, researchers propose that personalized tags can produce better search queries and recommendations. For example, a user might give a cat photo the tags (monty, pet, buddy, cat, chum). Clearly, the terms have personal meaning and can speak to what the user might really want to see in advertising and search results.

Researchers say the order in which the tags are ranked matter too. Currently, most search engines offer no direct way to learn and personalize a user’s preferences. Read more about how to change that in the April—June 2017 issue of IEEE MultiMedia. (Login may be required for full text.)


About Lori Cameron

Lori Cameron is a Senior Writer for the IEEE Computer Society and currently writes regular features for Computer magazine, Computing Edge, and the Computing Now and Magazine Roundup websites. Contact her at l.cameron@computer.org. Follow her on LinkedIn.

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