Effects of foraging in personalized content-based image recommendation
Affiliation
University of BedfordshireIssue Date
2019-06-30Subjects
Information Foraging Theoryinformation retrieval
recommendation system
G500 Information Systems
Metadata
Show full item recordAbstract
A major challenge of recommender systems is to help users locating interesting items. Personalized recommender systems have become very popular as they attempt to predetermine the needs of users and provide them with recommendations to personalize their navigation. However, few studies have addressed the question of what drives the users' attention to specific content within the collection and what influences the selection of interesting items. To this end, we employ the lens of Information Foraging Theory (IFT) to image recommendation to demonstrate how the user could utilize visual bookmarks to locate interesting images. We investigate a personalized content-based image recommendation system to understand what affects user attention by reinforcing visual attention cues based on IFT. We further find that visual bookmarks (cues) lead to a stronger scent of the recommended image collection. Our evaluation is based on the Pinterest image collection.Citation
Jaiswal AK, Liu H, Frommholz I (2019) 'Effects of foraging in personalized content-based image recommendation', , .Publisher
arXivAdditional Links
https://arxiv.org/abs/1907.00483Type
PreprintLanguage
enCollections
The following license files are associated with this item:
- Creative Commons
Except where otherwise noted, this item's license is described as http://creativecommons.org/licenses/by-nc-nd/4.0/