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WWW
2005
ACM
16 years 3 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»
15 years 4 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
15 years 23 days 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»
15 years 9 months 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
15 years 9 months 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...