Recommender systems have emerged as an effective decision tool to help users more easily and quickly find products that they prefer, especially in e-commerce environments. However, few studies have tried to understand how this technology has influenced the ...
Recommender systems have become important, as users are faced with an ever-increasing amount of information available on internet. Much of the research work on the topic has been focused on recommendation techniques, aiming at improving the accuracy of rec ...
Traditional websites have long relied on users revealing their preferences explicitly through direct manipulation interfaces. However recent recommender systems have gone as far as using implicit feedback indicators to understand users' interests. More tha ...
Critiquing-based recommender systems provide an efficient way for users to navigate through complex product spaces even if they are not familiar with the domain details in e-commerce environments. While recent research has mainly concentrated on methods fo ...
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Two music recommender websites, Pandora (a content-based recommender) and Last.fm (a rating-based social recommender), were compared side-by-side in a within-subject user study involving 64 participants. The main objective was to investigate users’ initial ...
