Effects of Foraging in Personalized Content-based Image Recommendation

TL;DR

This paper explores how visual cues based on Information Foraging Theory can enhance user attention and engagement in personalized content-based image recommendation systems, demonstrated through experiments on Pinterest data.

Contribution

It introduces a novel approach using visual bookmarks aligned with IFT to improve user attention and collection scent in image recommendations.

Findings

Visual bookmarks strengthen user attention to recommended images.

Reinforcing visual cues increases the scent of the image collection.

IFT-based cues improve navigation and interest in image recommendations.

Abstract

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.