How Users Perceive and Appraise Personalised Recommendations
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First we present Unison, a conceptual music recommender system for groups of people; the system aims at generating a playlist that takes musical tastes of all the group members into account. We discuss both theoretical and practical concerns related to suc ...
User interaction with online geospatial systems is an inter-disciplinary research field that combines the two disciplines Human Computer Interaction (HCI) and geographic information sciences. In recent years online geospatial systems have been created for ...
In this paper, we present an initial study of on-line unsupervised adaptation for face verification. To the authors’ knowledge this is the first study of this type. The key contributions consist of four test scenarios for the BANCA database as well as tw ...
Critiquing-based recommender systems elicit users' feedback, called critiques, which they made on the recommended items. This conversational style of interaction is in contract to the standard model where users receive recommendations in a single interacti ...
Our previous research indicates that using personality quizzes is a viable and promising way to build user profiles to recommend entertainment products. Based on these findings, our current research further investigates the feasibility of using personality ...
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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 ...
As e-commerce has evolved into its second generation, where the available products are becoming more complex and their abundance is almost unlimited, the task of locating a desired choice has become too difficult for the average user. Therefore, more effor ...
The size of digital libraries is increasing, making navigation and access to information more challenging. Improving the system by observing the users’ activities can help at providing better services to users of very large digital libraries. In this paper ...
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 ...
A critiquing-based recommender system acts like an artificial salesperson. It engages users in a conversational dialog where users can provide feedback in the form of critiques to the sample items that were shown to them. The feedback, in turn, enables the ...
