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» Putting Users in Control of their Recommendations
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RECSYS
2010
ACM
14 years 10 months ago
Group recommendations with rank aggregation and collaborative filtering
The majority of recommender systems are designed to make recommendations for individual users. However, in some circumstances the items to be selected are not intended for persona...
Linas Baltrunas, Tadas Makcinskas, Francesco Ricci
RECSYS
2009
ACM
15 years 4 months ago
Regret-based optimal recommendation sets in conversational recommender systems
Current conversational recommender systems are unable to offer guarantees on the quality of their recommendations due to a lack of principled user utility models. We develop an ap...
Paolo Viappiani, Craig Boutilier
ITRUST
2004
Springer
15 years 3 months ago
Analyzing Correlation between Trust and User Similarity in Online Communities
Abstract. Past evidence has shown that generic approaches to recommender systems based upon collaborative filtering tend to poorly scale. Moreover, their fitness for scenarios su...
Cai-Nicolas Ziegler, Georg Lausen
RECSYS
2009
ACM
15 years 4 months ago
Rate it again: increasing recommendation accuracy by user re-rating
A common approach to designing Recommender Systems (RS) consists of asking users to explicitly rate items in order to collect feedback about their preferences. However, users have...
Xavier Amatriain, Josep M. Pujol, Nava Tintarev, N...
RECSYS
2009
ACM
15 years 4 months ago
Conceptual recommender system for CiteSeerX
Short search engine queries do not provide contextual information, making it difficult for traditional search engines to understand what users are really requesting. One approach ...
Ajith Kodakateri Pudhiyaveetil, Susan Gauch, Hiep ...