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KDD
2007
ACM
191views Data Mining» more  KDD 2007»
14 years 8 months ago
Modeling relationships at multiple scales to improve accuracy of large recommender systems
The collaborative filtering approach to recommender systems predicts user preferences for products or services by learning past useritem relationships. In this work, we propose no...
Robert M. Bell, Yehuda Koren, Chris Volinsky
KDD
2003
ACM
129views Data Mining» more  KDD 2003»
14 years 8 months ago
Nantonac collaborative filtering: recommendation based on order responses
A recommender system suggests the items expected to be preferred by the users. Recommender systems use collaborative filtering to recommend items by summarizing the preferences of...
Toshihiro Kamishima
SIGIR
2011
ACM
12 years 10 months ago
Fast context-aware recommendations with factorization machines
The situation in which a choice is made is an important information for recommender systems. Context-aware recommenders take this information into account to make predictions. So ...
Steffen Rendle, Zeno Gantner, Christoph Freudentha...
PERCOM
2009
ACM
14 years 2 months ago
A Mobile Product Recommendation System Interacting with Tagged Products
— This paper presents a concept that enables consumers to access and share product recommendations using their mobile phone. Based on a review of current product recommendation m...
Felix von Reischach, Florian Michahelles, Dominiqu...
EPIA
2009
Springer
13 years 12 months ago
Item-Based and User-Based Incremental Collaborative Filtering for Web Recommendations
Abstract. In this paper we propose an incremental item-based collaborative filtering algorithm. It works with binary ratings (sometimes also called implicit ratings), as it is typi...
Catarina Miranda, Alípio Mário Jorge