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dc.contributor.authorJaiswal, Amit Kumaren
dc.contributor.authorLiu, Haimingen
dc.contributor.authorFrommholz, Ingoen
dc.date.accessioned2020-01-21T13:24:33Z
dc.date.available2020-01-21T13:24:33Z
dc.date.issued2019-06-30
dc.identifier.citationJaiswal AK, Liu H, Frommholz I (2019) 'Effects of foraging in personalized content-based image recommendation', , .en
dc.identifier.urihttp://hdl.handle.net/10547/623795
dc.description.abstractA 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.
dc.language.isoenen
dc.publisherarXiven
dc.relation.urlhttps://arxiv.org/abs/1907.00483en
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectInformation Foraging Theoryen
dc.subjectinformation retrievalen
dc.subjectrecommendation systemen
dc.subjectG500 Information Systemsen
dc.titleEffects of foraging in personalized content-based image recommendationen
dc.typePreprinten
dc.contributor.departmentUniversity of Bedfordshireen
dc.date.updated2020-01-21T13:22:20Z
html.description.abstractA 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.


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