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» A Lattice-Based Model for Recommender Systems
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ICDM
2008
IEEE
183views Data Mining» more  ICDM 2008»
15 years 6 months ago
Collaborative Filtering for Implicit Feedback Datasets
A common task of recommender systems is to improve customer experience through personalized recommendations based on prior implicit feedback. These systems passively track differe...
Yifan Hu, Yehuda Koren, Chris Volinsky
DEBU
2008
186views more  DEBU 2008»
14 years 12 months ago
A Survey of Collaborative Recommendation and the Robustness of Model-Based Algorithms
The open nature of collaborative recommender systems allows attackers who inject biased profile data to have a significant impact on the recommendations produced. Standard memory-...
Jeff J. Sandvig, Bamshad Mobasher, Robin D. Burke
CORR
2007
Springer
135views Education» more  CORR 2007»
14 years 12 months ago
AMIEDoT: An annotation model for document tracking and recommendation service
The primary objective of document annotation in whatever form, manual or electronic is to allow those who may not have control to original document to provide personal view on inf...
Charles A. Robert
KDD
2004
ACM
150views Data Mining» more  KDD 2004»
16 years 8 days ago
Complete This Puzzle: A Connectionist Approach to Accurate Web Recommendations Based on a Committee of Predictors
Abstract. We present a Context Ultra-Sensitive Approach based on two-step Recommender systems (CUSA-2step-Rec). Our approach relies on a committee of profile-specific neural networ...
Olfa Nasraoui, Mrudula Pavuluri
RECSYS
2009
ACM
15 years 6 months ago
Collaborative prediction and ranking with non-random missing data
A fundamental aspect of rating-based recommender systems is the observation process, the process by which users choose the items they rate. Nearly all research on collaborative ï¬...
Benjamin M. Marlin, Richard S. Zemel