NDLI: A recommender system that deals with items having an image as well as quantitative features

Content Provider	IEEE Xplore Digital Library
Author	Azodinia, M.R. Hajdu, A.
Copyright Year	2015
Description	Author affiliation: Dept. of Comput. Graphics & Image Process., Univ. of Debrecen, Debrecen, Hungary (Azodinia, M.R.; Hajdu, A.)
Abstract	A big part of data around us is in image format and people use these images in many of their decisions. The popularity of an item, in many cases, depends highly on its visual quality. For instance, the shape of a car has a significant influence on the attitude of potential customers toward it. Recommender systems try to provide people with recommendations resulted from an automatic process which is aimed at giving the users a better experience working with system, and perhaps improve the system owner's sales. As images are quite important in users' decisions, in this paper we have proposed a method to take images into account when trying to give the user a recommendation, which despite its apparent advantages has not found a fair amount of attention so far.
Starting Page	1
Ending Page	6
File Size	724672
Page Count	6
File Format	PDF
ISBN	9781479972531
DOI	10.1109/WISP.2015.7139167
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-05-15
Publisher Place	Italy
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Measurement collaborative filtering Mobile communication recommender systems hybrid Collaboration image retrieval prediction Motion pictures content-based filtering similarity metric Recommender systems Manganese
Content Type	Text
Resource Type	Article

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