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I3E
2008
234views Business» more  I3E 2008»
13 years 6 months ago
Development of Recommender Systems Using User Preference Tendencies: An Algorithm for Diversifying Recommendation
Abstract. Many e-commerce sites use a recommendation system to filter the specific information that a user wants out of an overload of information. Currently, the usefulness of the...
Yuki Ogawa, Hirohiko Suwa, Hitoshi Yamamoto, Isamu...
ECWEB
2010
Springer
155views ECommerce» more  ECWEB 2010»
13 years 3 months ago
Partial Ranking of Products for Recommendation Systems
A recommendation system (or recommender) is an algorithm whose goal is to recommend products to potential users. To achieve its task, it uses information about some user preference...
Sébastien Hémon, Thomas Largillier, ...
ESWS
2008
Springer
13 years 6 months ago
Semantic Reasoning: A Path to New Possibilities of Personalization
Abstract. Recommender systems face up to current information overload by selecting automatically items that match the personal preferences of each user. The so-called content-based...
Yolanda Blanco-Fernández, José J. Pa...
KDD
2012
ACM
187views Data Mining» more  KDD 2012»
11 years 7 months ago
Online learning to diversify from implicit feedback
In order to minimize redundancy and optimize coverage of multiple user interests, search engines and recommender systems aim to diversify their set of results. To date, these dive...
Karthik Raman, Pannaga Shivaswamy, Thorsten Joachi...
SIGKDD
2008
138views more  SIGKDD 2008»
13 years 5 months ago
Learning preferences of new users in recommender systems: an information theoretic approach
Recommender systems are a nice tool to help nd items of interest from an overwhelming number of available items. Collaborative Filtering (CF), the best known technology for recomme...
Al Mamunur Rashid, George Karypis, John Riedl