  User implicit feedback plays an important role in recommender systems.
However, finding implicit features is a tedious task. This paper aims to
identify users' preferences through implicit behavioural signals for image
recommendation based on the Information Scent Model of Information Foraging
Theory. In the first part, we hypothesise that the users' perception is
improved with visual cues in the images as behavioural signals that provide
users' information scent during information seeking. We designed a
content-based image recommendation system to explore which image attributes
(i.e., visual cues or bookmarks) help users find their desired image. We found
that users prefer recommendations predicated by visual cues and therefore
consider the visual cues as good information scent for their information
seeking. In the second part, we investigated if visual cues in the images
together with the images itself can be better perceived by the users than each
of them on its own. We evaluated the information scent artifacts in image
recommendation on the Pinterest image collection and the WikiArt dataset. We
find our proposed image recommendation system supports the implicit signals
through Information Foraging explanation of the information scent model.
