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» A Lattice-Based Model for Recommender Systems
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ESWA
2008
152views more  ESWA 2008»
14 years 12 months ago
Collaborative recommender systems: Combining effectiveness and efficiency
Recommender systems base their operation on past user ratings over a collection of items, for instance, books, CDs, etc. Collaborative filtering (CF) is a successful recommendatio...
Panagiotis Symeonidis, Alexandros Nanopoulos, Apos...
KDD
2009
ACM
162views Data Mining» more  KDD 2009»
16 years 12 days ago
TrustWalker: a random walk model for combining trust-based and item-based recommendation
Collaborative filtering is the most popular approach to build recommender systems and has been successfully employed in many applications. However, it cannot make recommendations ...
Mohsen Jamali, Martin Ester
EEE
2005
IEEE
15 years 5 months ago
Feature Selection Methods for Conversational Recommender Systems
This paper focuses on question selection methods for conversational recommender systems. We consider a scenario, where given an initial user query, the recommender system may ask ...
Nader Mirzadeh, Francesco Ricci, Mukesh Bansal
KDD
2010
ACM
265views Data Mining» more  KDD 2010»
15 years 3 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...
ITCC
2005
IEEE
15 years 5 months ago
A Web Recommendation System Based on Maximum Entropy
We propose a Web recommendation system based on a maximum entropy model. Under the maximum entropy principle, we can combine multiple levels of knowledge about users’ navigation...
Xin Jin, Bamshad Mobasher, Yanzan Zhou