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» Feature-Weighted User Model for Recommender Systems
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WISE
2010
Springer
13 years 5 months ago
Neighborhood-Restricted Mining and Weighted Application of Association Rules for Recommenders
Abstract. Association rule mining algorithms such as Apriori were originally developed to automatically detect patterns in sales transactions and were later on also successfully ap...
Fatih Gedikli, Dietmar Jannach
RECSYS
2010
ACM
13 years 8 months ago
Collaborative filtering via euclidean embedding
Recommendation systems suggest items based on user preferences. Collaborative filtering is a popular approach in which recommending is based on the rating history of the system. O...
Mohammad Khoshneshin, W. Nick Street
ICDIM
2010
IEEE
13 years 5 months ago
Social network collaborative filtering framework and online trust factors: A case study on Facebook
Recommender systems have been proposed to exploit the potential of social network by filtering the information and offer recommendations to a user that he is predicted to like. Co...
Wei Chen, Simon Fong
SDM
2010
SIAM
217views Data Mining» more  SDM 2010»
13 years 6 months ago
Collaborative Filtering: Weighted Nonnegative Matrix Factorization Incorporating User and Item Graphs
Collaborative filtering is an important topic in data mining and has been widely used in recommendation system. In this paper, we proposed a unified model for collaborative fil...
Quanquan Gu, Jie Zhou, Chris H. Q. Ding
IUI
2003
ACM
14 years 1 months ago
An adaptive stock tracker for personalized trading advice
The Stock Tracker is an adaptive recommendation system for trading stocks that automatically acquires content-based models of user preferences to tailor its buy and sell advice. T...
Jungsoon P. Yoo, Melinda T. Gervasio, Pat Langley