Searching for digital images on the web

The purpose of this paper is to examine the way in which end user searching on the web has become the primary method of locating digital images for many people. This paper seeks to investigate how users structure these image queries.

This study investigates the structure and formation of image queries on the web by mapping a sample of web queries to three known query classification schemes for image searching (i.e. Enser and McGregor, Jörgensen, and Chen).

The results indicate that the features and attributes of web image queries differ relative to image queries utilized on other information retrieval systems and by other user populations. This research points to the need for five additional attributes (i.e. collections, pornography, presentation, URL, and cost) in order to classify web image queries, which were not present in any of the three prior classification schemes.

Patterns in web searching for image content do emerge that inform the design of web‐based multimedia systems, namely, that there is a high interest in locating image collections by web searchers. Objects and people images are the predominant interest for web searchers. Cost is a factor for web searching. This knowledge of the structure of web image queries has implications for the design of image information retrieval systems and repositories, especially in the area of automatic tagging of images with metadata.

This is the first research that examines whether or not one can apply image query classifications schemes to web image queries.