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CIKM
2010
Springer
14 years 8 months ago
On bootstrapping recommender systems
Recommender systems perform much better on users for which they have more information. This gives rise to a problem of satisfying users new to a system. The problem is even more a...
Nadav Golbandi, Yehuda Koren, Ronny Lempel
SIGIR
2006
ACM
15 years 7 months ago
Personalized recommendation driven by information flow
We propose that the information access behavior of a group of people can be modeled as an information flow issue, in which people intentionally or unintentionally influence and in...
Xiaodan Song, Belle L. Tseng, Ching-Yung Lin, Ming...
UM
2010
Springer
15 years 6 months ago
Bayesian Credibility Modeling for Personalized Recommendation in Participatory Media
In this paper, we focus on the challenge that users face in processing messages on the web posted in participatory media settings, such as blogs. It is desirable to recommend to us...
Aaditeshwar Seth, Jie Zhang, Robin Cohen
KDD
2010
ACM
265views Data Mining» more  KDD 2010»
15 years 5 months ago
Combining predictions for accurate recommender systems
We analyze the application of ensemble learning to recommender systems on the Netflix Prize dataset. For our analysis we use a set of diverse state-of-the-art collaborative filt...
Michael Jahrer, Andreas Töscher, Robert Legen...
IIR
2010
15 years 3 months ago
Context-Dependent Recommendations with Items Splitting
Recommender systems are intelligent applications that help on-line users to tackle information overload by providing recommendations of relevant items. Collaborative Filtering (CF...
Linas Baltrunas, Francesco Ricci