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dc.contributor.authorJaiswal, Amit Kumar
dc.contributor.authorLiu, Haiming
dc.contributor.authorFrommholz, Ingo
dc.date.accessioned2020-07-07T11:08:09Z
dc.date.available2020-07-07T00:00:00Z
dc.date.available2020-07-07T11:08:09Z
dc.date.issued2019-12-31
dc.identifier.citationJaiswal AK, Liu H, Frommholz I (2019) 'Information foraging for enhancing implicit feedback in content-based image recommendation', 11th Forum for Information Retrieval Evaluation - Kolkata, ACM.en_US
dc.identifier.doi10.1145/3368567.3368583
dc.identifier.urihttp://hdl.handle.net/10547/624157
dc.description.abstractUser 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.en_US
dc.language.isoenen_US
dc.publisherACMen_US
dc.relation.urlhttps://dl.acm.org/doi/10.1145/3368567.3368583en_US
dc.relation.urlhttps://arxiv.org/abs/2001.06765en_US
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectcontent-based image recommendationen_US
dc.subjectinformation foragingen_US
dc.subjectSubject Categories::G500 Information Systemsen_US
dc.titleInformation foraging for enhancing implicit feedback in content-based image recommendationen_US
dc.typeConference papers, meetings and proceedingsen_US
dc.contributor.departmentUniversity of Bedfordshireen_US
dc.date.updated2020-07-07T11:04:45Z
dc.description.notefull text from arxiv


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Attribution-NonCommercial-NoDerivatives 4.0 International
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivatives 4.0 International