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WWW
2005
ACM
14 years 6 months ago
Improving recommendation lists through topic diversification
In this work we present topic diversification, a novel method designed to balance and diversify personalized recommendation lists in order to reflect the user's complete spec...
Cai-Nicolas Ziegler, Sean M. McNee, Joseph A. Kons...
I3E
2008
234views Business» more  I3E 2008»
13 years 7 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...
WEBI
2010
Springer
13 years 3 months ago
Reducing the Cold-Start Problem in Content Recommendation through Opinion Classification
Like search engines, recommender systems have become a tool that cannot be ignored by websites with a large selection of products, music, news or simply webpages links. The perform...
Damien Poirier, Françoise Fessant, Isabelle...
ICDM
2008
IEEE
99views Data Mining» more  ICDM 2008»
14 years 6 days ago
One-Class Collaborative Filtering
: © One-Class Collaborative Filtering Rong Pan, Yunhong Zhou, Bin Cao, Nathan N. Liu, Rajan Lukose, Martin Scholz, Qiang Yang HP Laboratories HPL-2008-133 collaborative filtering,...
Rong Pan, Yunhong Zhou, Bin Cao, Nathan Nan Liu, R...
CIDM
2007
IEEE
14 years 3 days ago
iScore: Measuring the Interestingness of Articles in a Limited User Environment
Abstract-Search engines, such as Google, assign scores to news articles based on their relevancy to a query. However, not all relevant articles for the query may be interesting to ...
Raymond K. Pon, Alfonso F. Cardenas, David Buttler...