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CISS
2008
IEEE
15 years 6 months ago
A lower-bound on the number of rankings required in recommender systems using collaborativ filtering
— We consider the situation where users rank items from a given set, and each user ranks only a (small) subset of all items. We assume that users can be classified into C classe...
Peter Marbach
UM
2010
Springer
15 years 4 months ago
A Study on User Perception of Personality-Based Recommender Systems
Our previous research indicates that using personality quizzes is a viable and promising way to build user profiles to recommend entertainment products. Based on these findings, ...
Rong Hu, Pearl Pu
AUSAI
2006
Springer
15 years 3 months ago
Incorporating Pageview Weight into an Association-Rule-Based Web Recommendation System
Web recommendation systems based on web usage mining try to mine users' behavior patterns from web access logs, and recommend pages to the online user by matching the user...
Liang Yan, Chunping Li
FLAIRS
2010
15 years 28 days ago
Assumption-Based Reasoning for Multiagent Case-Based Recommender Systems
Recommender systems (RSs) are popular tools dealing with information overload problems in eCommerce Web sites. RSs match user preferences with item representations and recommend t...
Fabiana Lorenzi, Francesco Ricci, Mara Abel, Ana L...
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...