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ACMICEC
2007
ACM
117views ECommerce» more  ACMICEC 2007»
13 years 11 months ago
Selectively acquiring ratings for product recommendation
Accurate prediction of customer preferences on products is the key to any recommender systems to realize its promised strategic values such as improved customer satisfaction and t...
Zan Huang
RECSYS
2010
ACM
13 years 7 months ago
Global budgets for local recommendations
We present the design, implementation and evaluation of a new geotagging service, Gloe, that makes it easy to find, rate and recommend arbitrary on-line content in a mobile settin...
Thomas Sandholm, Hang Ung, Christina Aperjis, Bern...
ECWEB
2011
Springer
233views ECommerce» more  ECWEB 2011»
12 years 7 months ago
Rating Elicitation Strategies for Collaborative Filtering
The accuracy of collaborative filtering recommender systems largely depends on two factors: the quality of the recommendation algorithm and the nature of the available item rating...
Mehdi Elahi, Valdemaras Repsys, Francesco Ricci
NSDI
2008
13 years 10 months ago
Using Salience Differentials to Making Visual Cues Noticeable
There is a large body of research on how to design user interfaces for systems so as to ensure that important messages from the systems are presented to the user to maximize the p...
Andreas P. Heiner, N. Asokan
RECSYS
2010
ACM
13 years 7 months ago
Multiverse recommendation: n-dimensional tensor factorization for context-aware collaborative filtering
Context has been recognized as an important factor to consider in personalized Recommender Systems. However, most model-based Collaborative Filtering approaches such as Matrix Fac...
Alexandros Karatzoglou, Xavier Amatriain, Linas Ba...